default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDGal Chechik
Person information
- affiliation: Stanford University, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2025
[c109]Eitan Shaar, Ariel Shaulov, Gal Chechik, Lior Wolf:
Adapting to the Unknown: Training-Free Audio-Visual Event Perception with Dynamic Thresholds. CVPR 2025: 3142-3151- [c108]Uri Gadot, Assaf Shocher, Shie Mannor, Gal Chechik, Assaf Hallak:
RL-RC-DoT: A Block-level RL agent for Task-Aware Video Compression. CVPR 2025: 12533-12542 - [c107]Lital Binyamin, Yoad Tewel, Hilit Segev, Eran Hirsch, Royi Rassin, Gal Chechik:
Make It Count: Text-to-Image Generation with an Accurate Number of Objects. CVPR 2025: 13242-13251 - [c106]Dana Cohen-Bar, Daniel Cohen-Or, Gal Chechik, Yoni Kasten:
TriTex: Learning Texture from a Single Mesh via Triplane Semantic Features. CVPR 2025: 21403-21413 - [c105]Ariel Shaulov, Tal Shaharabany, Eitan Shaar, Gal Chechik, Lior Wolf:
Classifier-Guided Captioning Across Modalities. ICASSP 2025: 1-5 - [c104]Dvir Samuel, Barak Meiri, Haggai Maron, Yoad Tewel, Nir Darshan, Shai Avidan, Gal Chechik, Rami Ben-Ari:
Lightning-Fast Image Inversion and Editing for Text-to-Image Diffusion Models. ICLR 2025 - [c103]Yoad Tewel, Rinon Gal, Dvir Samuel, Yuval Atzmon, Lior Wolf, Gal Chechik:
Add-it: Training-Free Object Insertion in Images With Pretrained Diffusion Models. ICLR 2025 - [c102]Michael Toker, Ido Galil, Hadas Orgad, Rinon Gal, Yoad Tewel, Gal Chechik, Yonatan Belinkov:
Padding Tone: A Mechanistic Analysis of Padding Tokens in T2I Models. NAACL (Long Papers) 2025: 7618-7632 - [i106]Ariel Shaulov, Tal Shaharabany, Eitan Shaar, Gal Chechik, Lior Wolf:
Classifier-Guided Captioning Across Modalities. CoRR abs/2501.03183 (2025) - [i105]Michael Toker, Ido Galil, Hadas Orgad, Rinon Gal, Yoad Tewel, Gal Chechik, Yonatan Belinkov:
Padding Tone: A Mechanistic Analysis of Padding Tokens in T2I Models. CoRR abs/2501.06751 (2025) - [i104]Uri Gadot, Assaf Shocher, Shie Mannor, Gal Chechik, Assaf Hallak:
RL-RC-DoT: A Block-level RL agent for Task-Aware Video Compression. CoRR abs/2501.12216 (2025) - [i103]Aviv Shamsian, Eitan Shaar, Aviv Navon, Gal Chechik, Ethan Fetaya:
Go Beyond Your Means: Unlearning with Per-Sample Gradient Orthogonalization. CoRR abs/2503.02312 (2025) - [i102]Eitan Shaar, Ariel Shaulov, Gal Chechik, Lior Wolf:
Adapting to the Unknown: Training-Free Audio-Visual Event Perception with Dynamic Thresholds. CoRR abs/2503.13693 (2025) - [i101]Guy Bar-Shalom, Fabrizio Frasca, Derek Lim, Yoav Gelberg, Yftah Ziser, Ran El-Yaniv, Gal Chechik, Haggai Maron:
Learning on LLM Output Signatures for gray-box LLM Behavior Analysis. CoRR abs/2503.14043 (2025) - [i100]Yair Shpitzer, Gal Chechik, Idan Schwartz:
Single Image Iterative Subject-driven Generation and Editing. CoRR abs/2503.16025 (2025) - [i99]Dana Cohen-Bar, Daniel Cohen-Or, Gal Chechik, Yoni Kasten:
TriTex: Learning Texture from a Single Mesh via Triplane Semantic Features. CoRR abs/2503.16630 (2025) - [i98]Dvir Samuel, Matan Levy, Nir Darshan, Gal Chechik, Rami Ben-Ari:
OmnimatteZero: Training-free Real-time Omnimatte with Pre-trained Video Diffusion Models. CoRR abs/2503.18033 (2025) - [i97]Ido Greenberg, Piotr Sielski, Hugo Linsenmaier, Rajesh Gandham, Shie Mannor, Alexandre Fender, Gal Chechik, Eli A. Meirom:
Accelerating Vehicle Routing via AI-Initialized Genetic Algorithms. CoRR abs/2504.06126 (2025) - [i96]Vignesh Balaji, Christos Kozyrakis, Gal Chechik, Haggai Maron:
Efficient GNN Training Through Structure-Aware Randomized Mini-Batching. CoRR abs/2504.18082 (2025) - [i95]Zhengyi Luo, Chen Tessler, Toru Lin, Ye Yuan, Tairan He, Wenli Xiao, Yunrong Guo, Gal Chechik, Kris Kitani, Linxi Fan, Yuke Zhu:
Emergent Active Perception and Dexterity of Simulated Humanoids from Visual Reinforcement Learning. CoRR abs/2505.12278 (2025) - [i94]Chen Tessler, Yifeng Jiang, Erwin Coumans, Zhengyi Luo, Gal Chechik, Xue Bin Peng:
MaskedManipulator: Versatile Whole-Body Control for Loco-Manipulation. CoRR abs/2505.19086 (2025) - [i93]Uri Gadot, Rinon Gal, Yftah Ziser, Gal Chechik, Shie Mannor:
Policy Optimized Text-to-Image Pipeline Design. CoRR abs/2505.21478 (2025) - [i92]Anum Afzal, Florian Matthes, Gal Chechik, Yftah Ziser:
Knowing Before Saying: LLM Representations Encode Information About Chain-of-Thought Success Before Completion. CoRR abs/2505.24362 (2025) - 2024
- [j30]Ohad Amosy, Tamuz Danzig, Ohad Lev, Ely Porat, Gal Chechik, Adi Makmal:
Iteration-Free quantum approximate optimization algorithm using neural networks. Quantum Mach. Intell. 6(2): 38 (2024) - [j29]Yoad Tewel
, Omri Kaduri, Rinon Gal, Yoni Kasten, Lior Wolf, Gal Chechik, Yuval Atzmon:
Training-Free Consistent Text-to-Image Generation. ACM Trans. Graph. 43(4): 52:1-52:18 (2024) - [j28]Chen Tessler, Yunrong Guo, Ofir Nabati, Gal Chechik, Xue Bin Peng:
MaskedMimic: Unified Physics-Based Character Control Through Masked Motion Inpainting. ACM Trans. Graph. 43(6): 209:1-209:21 (2024) - [c101]Dvir Samuel, Rami Ben-Ari, Simon Raviv, Nir Darshan, Gal Chechik:
Generating Images of Rare Concepts Using Pre-trained Diffusion Models. AAAI 2024: 4695-4703 - [c100]Rinon Gal, Yael Vinker, Yuval Alaluf, Amit Bermano, Daniel Cohen-Or, Ariel Shamir, Gal Chechik:
Breathing Life Into Sketches Using Text-to-Video Priors. CVPR 2024: 4325-4336 - [c99]Rinon Gal, Or Lichter, Elad Richardson, Or Patashnik, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or:
LCM-Lookahead for Encoder-Based Text-to-Image Personalization. ECCV (14) 2024: 322-340 - [c98]Assaf Hallak, Gal Dalal, Chen Tessler, Kelly Guo, Shie Mannor, Gal Chechik:
PlaMo: Plan and Move in Rich 3D Physical Environments. ECCV Workshops (2) 2024: 442-463 - [c97]Ohad Amosy, Tomer Volk, Eilam Shapira, Eyal Ben-David, Roi Reichart, Gal Chechik:
Text2Model: Text-based Model Induction for Zero-shot Image Classification. EMNLP (Findings) 2024: 155-172 - [c96]Idan Achituve, Idit Diamant, Arnon Netzer, Gal Chechik, Ethan Fetaya:
Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning. ICML 2024 - [c95]Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron:
Equivariant Deep Weight Space Alignment. ICML 2024 - [c94]Aviv Shamsian, Aviv Navon, David W. Zhang, Yan Zhang, Ethan Fetaya, Gal Chechik, Haggai Maron:
Improved Generalization of Weight Space Networks via Augmentations. ICML 2024 - [c93]Dvir Samuel, Rami Ben-Ari, Matan Levy, Nir Darshan, Gal Chechik:
Where's Waldo: Diffusion Features For Personalized Segmentation and Retrieval. NeurIPS 2024 - [c92]Omri Avrahami, Rinon Gal, Gal Chechik, Ohad Fried, Dani Lischinski, Arash Vahdat, Weili Nie:
DiffUHaul: A Training-Free Method for Object Dragging in Images. SIGGRAPH Asia 2024: 38:1-38:12 - [c91]Ohad Amosy, Gal Eyal, Gal Chechik:
Late to the party? On-demand unlabeled personalized federated learning. WACV 2024: 2173-2182 - [i91]Yoad Tewel, Omri Kaduri, Rinon Gal, Yoni Kasten, Lior Wolf, Gal Chechik, Yuval Atzmon:
Training-Free Consistent Text-to-Image Generation. CoRR abs/2402.03286 (2024) - [i90]Idan Achituve, Idit Diamant, Arnon Netzer, Gal Chechik, Ethan Fetaya:
Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning. CoRR abs/2402.04005 (2024) - [i89]Aviv Shamsian, Aviv Navon, David W. Zhang, Yan Zhang, Ethan Fetaya, Gal Chechik, Haggai Maron:
Improved Generalization of Weight Space Networks via Augmentations. CoRR abs/2402.04081 (2024) - [i88]Rinon Gal, Or Lichter, Elad Richardson, Or Patashnik, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or:
LCM-Lookahead for Encoder-based Text-to-Image Personalization. CoRR abs/2404.03620 (2024) - [i87]Simon Raviv, Gal Chechik:
Assessing Image Quality Using a Simple Generative Representation. CoRR abs/2404.18178 (2024) - [i86]Dvir Samuel, Rami Ben-Ari, Matan Levy, Nir Darshan, Gal Chechik:
Unveiling the Power of Diffusion Features For Personalized Segmentation and Retrieval. CoRR abs/2405.18025 (2024) - [i85]Ohad Rahamim, Hilit Segev, Idan Achituve, Yuval Atzmon, Yoni Kasten, Gal Chechik:
Lay-A-Scene: Personalized 3D Object Arrangement Using Text-to-Image Priors. CoRR abs/2406.00687 (2024) - [i84]Omri Avrahami, Rinon Gal, Gal Chechik, Ohad Fried, Dani Lischinski, Arash Vahdat, Weili Nie:
DiffUHaul: A Training-Free Method for Object Dragging in Images. CoRR abs/2406.01594 (2024) - [i83]Lital Binyamin, Yoad Tewel, Hilit Segev, Eran Hirsch, Royi Rassin, Gal Chechik:
Make It Count: Text-to-Image Generation with an Accurate Number of Objects. CoRR abs/2406.10210 (2024) - [i82]Assaf Hallak, Gal Dalal, Chen Tessler, Kelly Guo, Shie Mannor, Gal Chechik:
PlaMo: Plan and Move in Rich 3D Physical Environments. CoRR abs/2406.18237 (2024) - [i81]Guy Lutsker, Gal Sapir, Anastasia Godneva, Smadar Shilo, Jerry R. Greenfield, Dorit Samocha-Bonet, Shie Mannor, Eli Meirom, Gal Chechik, Hagai Rossman, Eran Segal:
From Glucose Patterns to Health Outcomes: A Generalizable Foundation Model for Continuous Glucose Monitor Data Analysis. CoRR abs/2408.11876 (2024) - [i80]Chen Tessler, Yunrong Guo, Ofir Nabati, Gal Chechik, Xue Bin Peng:
MaskedMimic: Unified Physics-Based Character Control Through Masked Motion Inpainting. CoRR abs/2409.14393 (2024) - [i79]Rinon Gal, Adi Haviv, Yuval Alaluf, Amit H. Bermano, Daniel Cohen-Or, Gal Chechik:
ComfyGen: Prompt-Adaptive Workflows for Text-to-Image Generation. CoRR abs/2410.01731 (2024) - [i78]Nikita Durasov, Assaf Shocher, Doruk Öner, Gal Chechik, Alexei A. Efros, Pascal Fua:
IT3: Idempotent Test-Time Training. CoRR abs/2410.04201 (2024) - [i77]Yoad Tewel, Rinon Gal, Dvir Samuel, Yuval Atzmon, Lior Wolf, Gal Chechik:
Add-it: Training-Free Object Insertion in Images With Pretrained Diffusion Models. CoRR abs/2411.07232 (2024) - [i76]Yuval Atzmon, Rinon Gal, Yoad Tewel, Yoni Kasten, Gal Chechik:
Multi-Shot Character Consistency for Text-to-Video Generation. CoRR abs/2412.07750 (2024) - [i75]Ohad Rahamim, Ori Malca, Dvir Samuel, Gal Chechik:
Bringing Objects to Life: 4D generation from 3D objects. CoRR abs/2412.20422 (2024) - 2023
- [j27]Rinon Gal, Moab Arar, Yuval Atzmon, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or:
Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models. ACM Trans. Graph. 42(4): 150:1-150:13 (2023) - [c90]Aviv Rosenberg, Assaf Hallak, Shie Mannor, Gal Chechik, Gal Dalal:
Planning and Learning with Adaptive Lookahead. AAAI 2023: 9606-9613 - [c89]Lior Bracha, Eitan Shaar, Aviv Shamsian, Ethan Fetaya, Gal Chechik:
DisCLIP: Open-Vocabulary Referring Expression Generation. BMVC 2023: 670-673 - [c88]Benjamin Fuhrer, Yuval Shpigelman, Chen Tessler, Shie Mannor, Gal Chechik, Eitan Zahavi, Gal Dalal:
Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs. CCGrid 2023: 331-343 - [c87]Tomer Volk, Eyal Ben-David, Ohad Amosy, Gal Chechik, Roi Reichart:
Example-based Hypernetworks for Multi-source Adaptation to Unseen Domains. EMNLP (Findings) 2023: 9096-9113 - [c86]Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit Haim Bermano, Gal Chechik, Daniel Cohen-Or:
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion. ICLR 2023 - [c85]Hilit Segev, Gal Chechik:
Personalized Federated Learning for Medical Segmentation using Hypernetworks. Tiny Papers @ ICLR 2023 - [c84]Yuval Atzmon, Eli A. Meirom, Shie Mannor, Gal Chechik:
Learning to Initiate and Reason in Event-Driven Cascading Processes. ICML 2023: 1218-1243 - [c83]Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron:
Graph Positional Encoding via Random Feature Propagation. ICML 2023: 9202-9223 - [c82]Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron:
Equivariant Architectures for Learning in Deep Weight Spaces. ICML 2023: 25790-25816 - [c81]Aviv Shamsian, Aviv Navon, Neta Glazer, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya:
Auxiliary Learning as an Asymmetric Bargaining Game. ICML 2023: 30689-30705 - [c80]Ido Greenberg, Shie Mannor, Gal Chechik, Eli A. Meirom:
Train Hard, Fight Easy: Robust Meta Reinforcement Learning. NeurIPS 2023 - [c79]Yoni Kasten, Ohad Rahamim, Gal Chechik:
Point Cloud Completion with Pretrained Text-to-Image Diffusion Models. NeurIPS 2023 - [c78]Royi Rassin, Eran Hirsch, Daniel Glickman, Shauli Ravfogel, Yoav Goldberg, Gal Chechik:
Linguistic Binding in Diffusion Models: Enhancing Attribute Correspondence through Attention Map Alignment. NeurIPS 2023 - [c77]Dvir Samuel, Rami Ben-Ari, Nir Darshan, Haggai Maron, Gal Chechik:
Norm-guided latent space exploration for text-to-image generation. NeurIPS 2023 - [c76]Yoad Tewel, Rinon Gal, Gal Chechik, Yuval Atzmon:
Key-Locked Rank One Editing for Text-to-Image Personalization. SIGGRAPH (Conference Paper Track) 2023: 12:1-12:11 - [c75]Chen Tessler, Yoni Kasten, Yunrong Guo, Shie Mannor, Gal Chechik, Xue Bin Peng:
CALM: Conditional Adversarial Latent Models for Directable Virtual Characters. SIGGRAPH (Conference Paper Track) 2023: 37:1-37:9 - [c74]Moab Arar, Rinon Gal, Yuval Atzmon, Gal Chechik, Daniel Cohen-Or, Ariel Shamir, Amit H. Bermano:
Domain-Agnostic Tuning-Encoder for Fast Personalization of Text-To-Image Models. SIGGRAPH Asia 2023: 72:1-72:10 - [c73]Idan Achituve, Gal Chechik, Ethan Fetaya:
Guided Deep Kernel Learning. UAI 2023: 11-21 - [i74]Ido Greenberg, Shie Mannor, Gal Chechik, Eli A. Meirom:
Train Hard, Fight Easy: Robust Meta Reinforcement Learning. CoRR abs/2301.11147 (2023) - [i73]Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron:
Equivariant Architectures for Learning in Deep Weight Spaces. CoRR abs/2301.12780 (2023) - [i72]Gal Dalal, Assaf Hallak, Gugan Thoppe, Shie Mannor, Gal Chechik:
SoftTreeMax: Exponential Variance Reduction in Policy Gradient via Tree Search. CoRR abs/2301.13236 (2023) - [i71]Aviv Shamsian, Aviv Navon, Neta Glazer, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya:
Auxiliary Learning as an Asymmetric Bargaining Game. CoRR abs/2301.13501 (2023) - [i70]Idan Achituve, Gal Chechik, Ethan Fetaya:
Guided Deep Kernel Learning. CoRR abs/2302.09574 (2023) - [i69]Rinon Gal, Moab Arar, Yuval Atzmon, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or:
Designing an Encoder for Fast Personalization of Text-to-Image Models. CoRR abs/2302.12228 (2023) - [i68]Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron:
Graph Positional Encoding via Random Feature Propagation. CoRR abs/2303.02918 (2023) - [i67]Dvir Samuel, Rami Ben-Ari, Simon Raviv, Nir Darshan, Gal Chechik:
It is all about where you start: Text-to-image generation with seed selection. CoRR abs/2304.14530 (2023) - [i66]Yoad Tewel, Rinon Gal, Gal Chechik, Yuval Atzmon:
Key-Locked Rank One Editing for Text-to-Image Personalization. CoRR abs/2305.01644 (2023) - [i65]Chen Tessler, Yoni Kasten, Yunrong Guo, Shie Mannor, Gal Chechik, Xue Bin Peng:
CALM: Conditional Adversarial Latent Models for Directable Virtual Characters. CoRR abs/2305.02195 (2023) - [i64]Lior Bracha, Eitan Shaar, Aviv Shamsian, Ethan Fetaya, Gal Chechik:
DisCLIP: Open-Vocabulary Referring Expression Generation. CoRR abs/2305.19108 (2023) - [i63]Dvir Samuel, Rami Ben-Ari, Nir Darshan, Haggai Maron, Gal Chechik:
Norm-guided latent space exploration for text-to-image generation. CoRR abs/2306.08687 (2023) - [i62]Royi Rassin, Eran Hirsch, Daniel Glickman, Shauli Ravfogel, Yoav Goldberg, Gal Chechik:
Linguistic Binding in Diffusion Models: Enhancing Attribute Correspondence through Attention Map Alignment. CoRR abs/2306.08877 (2023) - [i61]Yoni Kasten, Ohad Rahamim, Gal Chechik:
Point-Cloud Completion with Pretrained Text-to-image Diffusion Models. CoRR abs/2306.10533 (2023) - [i60]Moab Arar, Rinon Gal, Yuval Atzmon, Gal Chechik, Daniel Cohen-Or, Ariel Shamir, Amit H. Bermano:
Domain-Agnostic Tuning-Encoder for Fast Personalization of Text-To-Image Models. CoRR abs/2307.06925 (2023) - [i59]Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron:
Equivariant Deep Weight Space Alignment. CoRR abs/2310.13397 (2023) - [i58]Aviv Shamsian, David W. Zhang, Aviv Navon, Yan Zhang, Miltiadis Kofinas, Idan Achituve, Riccardo Valperga, Gertjan J. Burghouts, Efstratios Gavves, Cees G. M. Snoek, Ethan Fetaya, Gal Chechik, Haggai Maron:
Data Augmentations in Deep Weight Spaces. CoRR abs/2311.08851 (2023) - [i57]Rinon Gal, Yael Vinker, Yuval Alaluf, Amit H. Bermano, Daniel Cohen-Or, Ariel Shamir, Gal Chechik:
Breathing Life Into Sketches Using Text-to-Video Priors. CoRR abs/2311.13608 (2023) - [i56]Barak Meiri, Dvir Samuel, Nir Darshan, Gal Chechik, Shai Avidan, Rami Ben-Ari:
Fixed-point Inversion for Text-to-image diffusion models. CoRR abs/2312.12540 (2023) - 2022
- [j26]Chen Tessler, Yuval Shpigelman, Gal Dalal, Amit Mandelbaum, Doron Haritan Kazakov, Benjamin Fuhrer, Gal Chechik, Shie Mannor:
Reinforcement Learning for Datacenter Congestion Control. SIGMETRICS Perform. Evaluation Rev. 49(2): 43-46 (2022) - [j25]Rinon Gal, Or Patashnik, Haggai Maron, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or:
StyleGAN-NADA: CLIP-guided domain adaptation of image generators. ACM Trans. Graph. 41(4): 141:1-141:13 (2022) - [c72]Chen Tessler, Yuval Shpigelman, Gal Dalal, Amit Mandelbaum, Doron Haritan Kazakov, Benjamin Fuhrer, Gal Chechik, Shie Mannor:
Reinforcement Learning for Datacenter Congestion Control. AAAI 2022: 12615-12621 - [c71]Roei Herzig, Elad Ben-Avraham, Karttikeya Mangalam, Amir Bar, Gal Chechik, Anna Rohrbach, Trevor Darrell, Amir Globerson:
Object-Region Video Transformers. CVPR 2022: 3138-3149 - [c70]Amir Bar, Xin Wang, Vadim Kantorov, Colorado J. Reed, Roei Herzig, Gal Chechik, Anna Rohrbach, Trevor Darrell, Amir Globerson:
DETReg: Unsupervised Pretraining with Region Priors for Object Detection. CVPR 2022: 14585-14595 - [c69]Niv Cohen, Rinon Gal, Eli A. Meirom, Gal Chechik, Yuval Atzmon:
"This Is My Unicorn, Fluffy": Personalizing Frozen Vision-Language Representations. ECCV (20) 2022: 558-577 - [c68]Guy Tennenholtz, Assaf Hallak, Gal Dalal, Shie Mannor, Gal Chechik, Uri Shalit:
On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning. ICLR 2022 - [c67]Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik:
Optimizing Tensor Network Contraction Using Reinforcement Learning. ICML 2022: 15278-15292 - [c66]Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya:
Multi-Task Learning as a Bargaining Game. ICML 2022: 16428-16446 - [c65]Guy Tennenholtz, Nadav Merlis, Lior Shani, Shie Mannor, Uri Shalit, Gal Chechik, Assaf Hallak, Gal Dalal:
Reinforcement Learning with a Terminator. NeurIPS 2022 - [c64]Ohad Amosy, Gal Chechik:
Coupled Training for Multi-Source Domain Adaptation. WACV 2022: 1071-1080 - [i55]Or Litany, Haggai Maron, David Acuna, Jan Kautz, Gal Chechik, Sanja Fidler:
Federated Learning with Heterogeneous Architectures using Graph HyperNetworks. CoRR abs/2201.08459 (2022) - [i54]Aviv Rosenberg, Assaf Hallak, Shie Mannor, Gal Chechik, Gal Dalal:
Planning and Learning with Adaptive Lookahead. CoRR abs/2201.12403 (2022) - [i53]Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya:
Multi-Task Learning as a Bargaining Game. CoRR abs/2202.01017 (2022) - [i52]Yuval Atzmon, Eli A. Meirom, Shie Mannor, Gal Chechik:
Learning to reason about and to act on physical cascading events. CoRR abs/2202.01108 (2022) - [i51]Tomer Volk, Eyal Ben-David, Ohad Amosy, Gal Chechik, Roi Reichart:
Example-based Hypernetworks for Out-of-Distribution Generalization. CoRR abs/2203.14276 (2022) - [i50]Niv Cohen, Rinon Gal, Eli A. Meirom, Gal Chechik, Yuval Atzmon:
"This is my unicorn, Fluffy": Personalizing frozen vision-language representations. CoRR abs/2204.01694 (2022) - [i49]Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik:
Optimizing Tensor Network Contraction Using Reinforcement Learning. CoRR abs/2204.09052 (2022) - [i48]Guy Tennenholtz, Nadav Merlis, Lior Shani, Shie Mannor, Uri Shalit, Gal Chechik, Assaf Hallak, Gal Dalal:
Reinforcement Learning with a Terminator. CoRR abs/2205.15376 (2022) - [i47]Benjamin Fuhrer, Yuval Shpigelman, Chen Tessler, Shie Mannor, Gal Chechik, Eitan Zahavi, Gal Dalal:
Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs. CoRR abs/2207.02295 (2022) - [i46]Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or:
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion. CoRR abs/2208.01618 (2022) - [i45]Gal Dalal, Assaf Hallak, Shie Mannor, Gal Chechik:
SoftTreeMax: Policy Gradient with Tree Search. CoRR abs/2209.13966 (2022) - [i44]Ohad Amosy, Tomer Volk, Eyal Ben-David, Roi Reichart, Gal Chechik:
Text2Model: Model Induction for Zero-shot Generalization Using Task Descriptions. CoRR abs/2210.15182 (2022) - 2021
- [c63]Renana Opochinsky, Gal Chechik, Sharon Gannot:
Deep Ranking-Based DOA Tracking Algorithm. EUSIPCO 2021: 1020-1024 - [c62]Dvir Samuel, Gal Chechik:
Distributional Robustness Loss for Long-tail Learning. ICCV 2021: 9475-9484 - [c61]Sangho Lee, Jiwan Chung, Youngjae Yu, Gunhee Kim, Thomas M. Breuel, Gal Chechik, Yale Song:
ACAV100M: Automatic Curation of Large-Scale Datasets for Audio-Visual Video Representation Learning. ICCV 2021: 10254-10264 - [c60]Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya:
Auxiliary Learning by Implicit Differentiation. ICLR 2021 - [c59]Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik:
Learning the Pareto Front with Hypernetworks. ICLR 2021 - [c58]Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya:
GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning. ICML 2021: 54-65 - [c57]Amir Bar, Roei Herzig, Xiaolong Wang, Anna Rohrbach, Gal Chechik, Trevor Darrell, Amir Globerson:
Compositional Video Synthesis with Action Graphs. ICML 2021: 662-673 - [c56]Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik:
Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks. ICML 2021: 7565-7577 - [c55]Aviv Shamsian, Aviv Navon, Ethan Fetaya, Gal Chechik:
Personalized Federated Learning using Hypernetworks. ICML 2021: 9489-9502 - [c54]Gilad Yehudai, Ethan Fetaya, Eli A. Meirom, Gal Chechik, Haggai Maron:
From Local Structures to Size Generalization in Graph Neural Networks. ICML 2021: 11975-11986 - [c53]Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya:
On Learning Sets of Symmetric Elements (Extended Abstract). IJCAI 2021: 4794-4798 - [c52]Gal Dalal, Assaf Hallak, Steven Dalton, Iuri Frosio, Shie Mannor, Gal Chechik:
Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction. NeurIPS 2021: 5518-5530 - [c51]Idan Achituve, Aviv Shamsian, Aviv Navon, Gal Chechik, Ethan Fetaya:
Personalized Federated Learning With Gaussian Processes. NeurIPS 2021: 8392-8406 - [c50]Harsh Agrawal, Eli A. Meirom, Yuval Atzmon, Shie Mannor, Gal Chechik:
Known unknowns: Learning novel concepts using reasoning-by-elimination. UAI 2021: 504-514 - [c49]Idan Achituve, Haggai Maron, Gal Chechik:
Self-Supervised Learning for Domain Adaptation on Point Clouds. WACV 2021: 123-133 - [c48]Dvir Samuel, Yuval Atzmon, Gal Chechik:
From generalized zero-shot learning to long-tail with class descriptors. WACV 2021: 286-295 - [i43]Sangho Lee, Jiwan Chung, Youngjae Yu, Gunhee Kim, Thomas M. Breuel, Gal Chechik, Yale Song:
Automatic Curation of Large-Scale Datasets for Audio-Visual Representation Learning. CoRR abs/2101.10803 (2021) - [i42]Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya:
GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning. CoRR abs/2102.07868 (2021) - [i41]Chen Tessler, Yuval Shpigelman, Gal Dalal, Amit Mandelbaum, Doron Haritan Kazakov, Benjamin Fuhrer, Gal Chechik, Shie Mannor:
Reinforcement Learning for Datacenter Congestion Control. CoRR abs/2102.09337 (2021) - [i40]Aviv Shamsian, Aviv Navon, Ethan Fetaya, Gal Chechik:
Personalized Federated Learning using Hypernetworks. CoRR abs/2103.04628 (2021) - [i39]Dvir Samuel, Gal Chechik:
Distributional Robustness Loss for Long-tail Learning. CoRR abs/2104.03066 (2021) - [i38]Amir Bar, Xin Wang, Vadim Kantorov, Colorado J. Reed, Roei Herzig, Gal Chechik, Anna Rohrbach, Trevor Darrell, Amir Globerson:
DETReg: Unsupervised Pretraining with Region Priors for Object Detection. CoRR abs/2106.04550 (2021) - [i37]Idan Achituve, Aviv Shamsian, Aviv Navon, Gal Chechik, Ethan Fetaya:
Personalized Federated Learning with Gaussian Processes. CoRR abs/2106.15482 (2021) - [i36]Assaf Hallak, Gal Dalal, Steven Dalton, Iuri Frosio, Shie Mannor, Gal Chechik:
Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction. CoRR abs/2107.01715 (2021) - [i35]Rinon Gal, Or Patashnik, Haggai Maron, Gal Chechik, Daniel Cohen-Or:
StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators. CoRR abs/2108.00946 (2021) - [i34]Guy Tennenholtz, Assaf Hallak, Gal Dalal, Shie Mannor, Gal Chechik, Uri Shalit:
On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning. CoRR abs/2110.06539 (2021) - [i33]Roei Herzig, Elad Ben-Avraham, Karttikeya Mangalam, Amir Bar, Gal Chechik, Anna Rohrbach, Trevor Darrell, Amir Globerson:
Object-Region Video Transformers. CoRR abs/2110.06915 (2021) - [i32]Ohad Amosy, Gal Eyal, Gal Chechik:
Inference-Time Personalized Federated Learning. CoRR abs/2111.08356 (2021) - 2020
- [c47]Aviv Shamsian, Ofri Kleinfeld, Amir Globerson, Gal Chechik:
Learning Object Permanence from Video. ECCV (16) 2020: 35-50 - [c46]Roei Herzig, Amir Bar, Huijuan Xu, Gal Chechik, Trevor Darrell, Amir Globerson:
Learning Canonical Representations for Scene Graph to Image Generation. ECCV (26) 2020: 210-227 - [c45]Tanmay Gupta, Arash Vahdat, Gal Chechik, Xiaodong Yang, Jan Kautz, Derek Hoiem:
Contrastive Learning for Weakly Supervised Phrase Grounding. ECCV (3) 2020: 752-768 - [c44]Tzuf Paz-Argaman, Reut Tsarfaty, Gal Chechik, Yuval Atzmon:
ZEST: Zero-shot Learning from Text Descriptions using Textual Similarity and Visual Summarization. EMNLP (Findings) 2020: 569-579 - [c43]Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya:
On Learning Sets of Symmetric Elements. ICML 2020: 6734-6744 - [c42]Yuval Atzmon, Felix Kreuk, Uri Shalit, Gal Chechik:
A causal view of compositional zero-shot recognition. NeurIPS 2020 - [c41]Moshiko Raboh, Roei Herzig, Jonathan Berant, Gal Chechik, Amir Globerson:
Differentiable Scene Graphs. WACV 2020: 1477-1486 - [i31]Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya:
On Learning Sets of Symmetric Elements. CoRR abs/2002.08599 (2020) - [i30]Aviv Shamsian, Ofri Kleinfeld, Amir Globerson, Gal Chechik:
Learning Object Permanence from Video. CoRR abs/2003.10469 (2020) - [i29]Idan Achituve, Haggai Maron, Gal Chechik:
Self-Supervised Learning for Domain Adaptation on Point-Clouds. CoRR abs/2003.12641 (2020) - [i28]Dvir Samuel, Yuval Atzmon, Gal Chechik:
Long-tail learning with attributes. CoRR abs/2004.02235 (2020) - [i27]Tanmay Gupta, Arash Vahdat, Gal Chechik, Xiaodong Yang, Jan Kautz, Derek Hoiem:
Contrastive Learning for Weakly Supervised Phrase Grounding. CoRR abs/2006.09920 (2020) - [i26]Yuval Atzmon, Felix Kreuk, Uri Shalit, Gal Chechik:
A causal view of compositional zero-shot recognition. CoRR abs/2006.14610 (2020) - [i25]Amir Bar, Roei Herzig, Xiaolong Wang, Gal Chechik, Trevor Darrell, Amir Globerson:
Compositional Video Synthesis with Action Graphs. CoRR abs/2006.15327 (2020) - [i24]Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya:
Auxiliary Learning by Implicit Differentiation. CoRR abs/2007.02693 (2020) - [i23]Achiya Jerbi, Roei Herzig, Jonathan Berant, Gal Chechik, Amir Globerson:
Learning Object Detection from Captions via Textual Scene Attributes. CoRR abs/2009.14558 (2020) - [i22]Tzuf Paz-Argaman, Yuval Atzmon, Gal Chechik, Reut Tsarfaty:
ZEST: Zero-shot Learning from Text Descriptions using Textual Similarity and Visual Summarization. CoRR abs/2010.03276 (2020) - [i21]Aviv Navon, Aviv Shamsian, Gal Chechik, Ethan Fetaya:
Learning the Pareto Front with Hypernetworks. CoRR abs/2010.04104 (2020) - [i20]Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik:
How to Stop Epidemics: Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks. CoRR abs/2010.05313 (2020) - [i19]Gilad Yehudai, Ethan Fetaya, Eli A. Meirom, Gal Chechik, Haggai Maron:
On Size Generalization in Graph Neural Networks. CoRR abs/2010.08853 (2020) - [i18]Ohad Amosy, Gal Chechik:
Teacher-Student Consistency For Multi-Source Domain Adaptation. CoRR abs/2010.10054 (2020)
2010 – 2019
- 2019
- [c40]Roman Visotsky, Yuval Atzmon, Gal Chechik:
Learning with Per-Sample Side Information. AGI 2019: 209-219 - [c39]Yuval Atzmon, Gal Chechik:
Adaptive Confidence Smoothing for Generalized Zero-Shot Learning. CVPR 2019: 11671-11680 - [c38]Lior Bracha, Gal Chechik:
Informative Object Annotations: Tell Me Something I Don't Know. CVPR 2019: 12507-12515 - [c37]Hagai Taitelbaum, Gal Chechik, Jacob Goldberger:
Multilingual word translation using auxiliary languages. EMNLP/IJCNLP (1) 2019: 1330-1335 - [c36]Hagai Taitelbaum, Gal Chechik, Jacob Goldberger:
A Multi-Pairwise Extension of Procrustes Analysis for Multilingual Word Translation. EMNLP/IJCNLP (1) 2019: 3558-3563 - [c35]Hagai Taitelbaum, Gal Chechik, Jacob Goldberger:
Network Adaptation Strategies for Learning New Classes without Forgetting the Original Ones. ICASSP 2019: 3637-3641 - [c34]Gilad Vered, Gal Oren, Yuval Atzmon, Gal Chechik:
Joint Optimization for Cooperative Image Captioning. ICCV 2019: 8897-8906 - [c33]Renana Opochinsky, Bracha Laufer-Goldshtein, Sharon Gannot, Gal Chechik:
Deep Ranking-Based Sound Source Localization. WASPAA 2019: 283-287 - [i17]Moshiko Raboh, Roei Herzig, Gal Chechik, Jonathan Berant, Amir Globerson:
Learning Latent Scene-Graph Representations for Referring Relationships. CoRR abs/1902.10200 (2019) - [i16]Roman Visotsky, Yuval Atzmon, Gal Chechik:
Few-Shot Learning with Per-Sample Rich Supervision. CoRR abs/1906.03859 (2019) - [i15]Gilad Vered, Gal Oren, Yuval Atzmon, Gal Chechik:
Cooperative image captioning. CoRR abs/1907.11565 (2019) - [i14]Roei Herzig, Amir Bar, Huijuan Xu, Gal Chechik, Trevor Darrell, Amir Globerson:
Learning Canonical Representations for Scene Graph to Image Generation. CoRR abs/1912.07414 (2019) - 2018
- [c32]Roei Herzig, Moshiko Raboh, Gal Chechik, Jonathan Berant, Amir Globerson:
Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction. NeurIPS 2018: 7211-7221 - [c31]Yuval Atzmon, Gal Chechik:
Probabilistic AND-OR Attribute Grouping for Zero-Shot Learning. UAI 2018: 382-392 - [i13]Roei Herzig, Moshiko Raboh, Gal Chechik, Jonathan Berant, Amir Globerson:
Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction. CoRR abs/1802.05451 (2018) - [i12]Yuval Atzmon, Gal Chechik:
Probabilistic AND-OR Attribute Grouping for Zero-Shot Learning. CoRR abs/1806.02664 (2018) - [i11]Yair Lakretz, Gal Chechik, Evan-Gary Cohen, Alessandro Treves, Naama Friedmann:
Metric Learning for Phoneme Perception. CoRR abs/1809.07824 (2018) - [i10]Yuval Atzmon, Gal Chechik:
Domain-Aware Generalized Zero-Shot Learning. CoRR abs/1812.09903 (2018) - [i9]Lior Bracha, Gal Chechik:
Informative Object Annotations: Tell Me Something I Don't Know. CoRR abs/1812.10358 (2018) - 2017
- [j24]Alon Zweig, Gal Chechik:
Group online adaptive learning. Mach. Learn. 106(9-10): 1747-1770 (2017) - [c30]Ramakrishna Vedantam, Samy Bengio, Kevin Murphy, Devi Parikh, Gal Chechik:
Context-Aware Captions from Context-Agnostic Supervision. CVPR 2017: 1070-1079 - [c29]Andreas Veit, Neil Alldrin, Gal Chechik, Ivan Krasin, Abhinav Gupta, Serge J. Belongie:
Learning from Noisy Large-Scale Datasets with Minimal Supervision. CVPR 2017: 6575-6583 - [c28]Ido Cohen, Eli (Omid) David, Nathan S. Netanyahu, Noa Liscovitch, Gal Chechik:
DeepBrain: Functional Representation of Neural In-Situ Hybridization Images for Gene Ontology Classification Using Deep Convolutional Autoencoders. ICANN (2) 2017: 287-296 - [c27]Qifan Wang, Gal Chechik, Chen Sun, Bin Shen:
Instance-Level Label Propagation with Multi-Instance Learning. IJCAI 2017: 2943-2949 - [i8]Andreas Veit, Neil Alldrin, Gal Chechik, Ivan Krasin, Abhinav Gupta, Serge J. Belongie:
Learning From Noisy Large-Scale Datasets With Minimal Supervision. CoRR abs/1701.01619 (2017) - [i7]Ramakrishna Vedantam, Samy Bengio, Kevin Murphy, Devi Parikh, Gal Chechik:
Context-aware Captions from Context-agnostic Supervision. CoRR abs/1701.02870 (2017) - [i6]Ido Cohen, Eli David, Nathan S. Netanyahu, Noa Liscovitch, Gal Chechik:
DeepBrain: Functional Representation of Neural In-Situ Hybridization Images for Gene Ontology Classification Using Deep Convolutional Autoencoders. CoRR abs/1711.09663 (2017) - 2016
- [j23]Lior Kirsch, Gal Chechik:
On Expression Patterns and Developmental Origin of Human Brain Regions. PLoS Comput. Biol. 12(8) (2016) - [i5]Yuval Atzmon, Jonathan Berant, Vahid Kezami, Amir Globerson, Gal Chechik:
Learning to generalize to new compositions in image understanding. CoRR abs/1608.07639 (2016) - 2015
- [j22]Ossnat Bar-Shira, Ronnie Maor, Gal Chechik:
Gene Expression Switching of Receptor Subunits in Human Brain Development. PLoS Comput. Biol. 11(12) (2015) - [c26]Yair Lakretz, Gal Chechik, Naama Friedmann, Michal Rosen-Zvi:
Probabilistic Graphical Models of Dyslexia. KDD 2015: 1919-1928 - [c25]Yuval Atzmon, Uri Shalit, Gal Chechik:
Learning Sparse Metrics, One Feature at a Time. FE@NIPS 2015: 30-48 - [c24]Alexander Kalmanovich, Gal Chechik:
Gradual Training Method for Denoising Auto Encoders. ICLR (Workshop) 2015 - 2014
- [j21]Grégoire Mesnil, Antoine Bordes, Jason Weston, Gal Chechik, Yoshua Bengio:
Learning semantic representations of objects and their parts. Mach. Learn. 94(2): 281-301 (2014) - [c23]Uri Shalit, Gal Chechik:
Coordinate-descent for learning orthogonal matrices through Givens rotations. ICML 2014: 548-556 - [i4]Alexander Kalmanovich, Gal Chechik:
Gradual training of deep denoising auto encoders. CoRR abs/1412.6257 (2014) - 2013
- [j20]Noa Liscovitch, Uri Shalit, Gal Chechik:
FuncISH: learning a functional representation of neural ISH images. Bioinform. 29(13): 36-43 (2013) - [j19]Noa Liscovitch, Gal Chechik:
Specialization of Gene Expression during Mouse Brain Development. PLoS Comput. Biol. 9(9) (2013) - [c22]Uri Shalit, Daphna Weinshall, Gal Chechik:
Modeling Musical Influence with Topic Models. ICML (2) 2013: 244-252 - [i3]Uri Shalit, Gal Chechik:
Efficient coordinate-descent for orthogonal matrices through Givens rotations. CoRR abs/1312.0624 (2013) - 2012
- [j18]Uri Shalit, Daphna Weinshall, Gal Chechik:
Online Learning in the Embedded Manifold of Low-rank Matrices. J. Mach. Learn. Res. 13: 429-458 (2012) - [j17]Lior Kirsch, Noa Liscovitch, Gal Chechik:
Localizing Genes to Cerebellar Layers by Classifying ISH Images. PLoS Comput. Biol. 8(12) (2012) - [c21]Koby Crammer, Gal Chechik:
Adaptive Regularization for Similarity Measures. ICML 2012 - [i2]Koby Crammer, Gal Chechik:
Adaptive Regularization for Weight Matrices. CoRR abs/1206.4639 (2012) - [i1]Amir Globerson, Gal Chechik, Naftali Tishby:
Sufficient Dimensionality Reduction with Irrelevant Statistics. CoRR abs/1212.2483 (2012) - 2011
- [c20]Richard F. Lyon, Jay Ponte, Gal Chechik:
Sparse coding of auditory features for machine hearing in interference. ICASSP 2011: 5876-5879 - 2010
- [j16]Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio:
Large Scale Online Learning of Image Similarity Through Ranking. J. Mach. Learn. Res. 11: 1109-1135 (2010) - [j15]Richard F. Lyon, Martin Rehn, Samy Bengio, Thomas C. Walters, Gal Chechik:
Sound Retrieval and Ranking Using Sparse Auditory Representations. Neural Comput. 22(9): 2390-2416 (2010) - [c19]Geremy Heitz, Gal Chechik:
Object separation in x-ray image sets. CVPR 2010: 2093-2100 - [c18]Uri Shalit, Daphna Weinshall, Gal Chechik:
Online Learning in The Manifold of Low-Rank Matrices. NIPS 2010: 2128-2136
2000 – 2009
- 2009
- [j14]Gal Chechik, Daphne Koller:
Timing of Gene Expression Responses to Environmental Changes. J. Comput. Biol. 16(2): 279-290 (2009) - [c17]Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio:
Large Scale Online Learning of Image Similarity through Ranking. IbPRIA 2009: 11-14 - [c16]Gal Chechik, Uri Shalit, Varun Sharma, Samy Bengio:
An Online Algorithm for Large Scale Image Similarity Learning. NIPS 2009: 306-314 - 2008
- [j13]Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller:
Max-margin Classification of Data with Absent Features. J. Mach. Learn. Res. 9: 1-21 (2008) - [c15]Gal Chechik, Eugene Ie, Martin Rehn, Samy Bengio, Dick Lyon:
Large-scale content-based audio retrieval from text queries. Multimedia Information Retrieval 2008: 105-112 - 2007
- [j12]Gal Chechik, Christina S. Leslie, William Stafford Noble, Gunnar Rätsch, Quaid Morris, Koji Tsuda:
NIPS workshop on New Problems and Methods in Computational Biology. BMC Bioinform. 8(S-10) (2007) - [j11]Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby:
Euclidean Embedding of Co-occurrence Data. J. Mach. Learn. Res. 8: 2265-2295 (2007) - 2006
- [j10]Sean O'Rourke, Gal Chechik, Robin Friedman, Eleazar Eskin:
Discrete profile comparison using information bottleneck. BMC Bioinform. 7(S-1) (2006) - [c14]Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby:
Embedding Heterogeneous Data Using Statistical Models. AAAI 2006: 1605-1608 - [c13]Alexis J. Battle, Gal Chechik, Daphne Koller:
Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks. NIPS 2006: 121-128 - [c12]Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller:
Max-margin classification of incomplete data. NIPS 2006: 233-240 - 2005
- [j9]Israel Nelken, Gal Chechik, Thomas D. Mrsic-Flogel, Andrew J. King, Jan W. H. Schnupp:
Encoding Stimulus Information by Spike Numbers and Mean Response Time in Primary Auditory Cortex. J. Comput. Neurosci. 19(2): 199-221 (2005) - [j8]Gal Chechik, Amir Globerson, Naftali Tishby, Yair Weiss:
Information Bottleneck for Gaussian Variables. J. Mach. Learn. Res. 6: 165-188 (2005) - 2004
- [c11]Koby Crammer, Gal Chechik:
A needle in a haystack: local one-class optimization. ICML 2004 - [c10]Amir Globerson, Gal Chechik, Fernando C. N. Pereira, Naftali Tishby:
Euclidean Embedding of Co-Occurrence Data. NIPS 2004: 497-504 - [c9]Sean O'Rourke, Gal Chechik, Robin Friedman, Eleazar Eskin:
Discrete profile alignment via constrained information bottleneck. NIPS 2004: 1009-1016 - 2003
- [j7]Gal Chechik:
Spike-Timing-Dependent Plasticity and Relevant Mutual Information Maximization. Neural Comput. 15(7): 1481-1510 (2003) - [c8]Hezi Avraham, Gal Chechik, Eytan Ruppin:
Are There Representations in Embodied Evolved Agents? Taking Measures. ECAL 2003: 743-752 - [c7]Gal Chechik, Amir Globerson, Naftali Tishby, Yair Weiss:
Information Bottleneck for Gaussian Variables. NIPS 2003: 1213-1220 - [c6]Amir Globerson, Gal Chechik, Naftali Tishby:
Sufficient Dimensionality Reduction with Irrelevance Statistics. UAI 2003: 281-288 - 2002
- [c5]Gal Chechik, Naftali Tishby:
Extracting Relevant Structures with Side Information. NIPS 2002: 857-864 - 2001
- [j6]Gal Chechik:
Spike timing dependent plasticity and mutual information in spiking neurons. Neurocomputing 38-40: 147-152 (2001) - [j5]Gal Chechik, Isaac Meilijson, Eytan Ruppin:
Effective Neuronal Learning with Ineffective Hebbian Learning Rules. Neural Comput. 13(4): 817-840 (2001) - [c4]Gal Chechik, Amir Globerson, Michael J. Anderson, Eric D. Young, Israel Nelken, Naftali Tishby:
Group Redundancy Measures Reveal Redundancy Reduction in the Auditory Pathway. NIPS 2001: 173-180 - 2000
- [j4]Gal Chechik, Isaac Meilijson, Eytan Ruppin:
Neuronal normalization provides effective learning through ineffective synaptic learning rules. Neurocomputing 32-33: 345-351 (2000) - [c3]Gal Chechik, Naftali Tishby:
Temporally Dependent Plasticity: An Information Theoretic Account. NIPS 2000: 110-116
1990 – 1999
- 1999
- [j3]Gal Chechik, Isaac Meilijson, Eytan Ruppin:
Neuronal regulation: A biologically plausible mechanism for efficient synaptic pruning in development. Neurocomputing 26-27: 633-639 (1999) - [j2]Gal Chechik, Isaac Meilijson, Eytan Ruppin:
Neuronal Regulation: A Mechanism for Synaptic Pruning During Brain Maturation. Neural Comput. 11(8): 2061-2080 (1999) - [c2]Gal Chechik, Isaac Meilijson, Eytan Ruppin:
Effective Learning Requires Neuronal Remodeling of Hebbian Synapses. NIPS 1999: 96-102 - 1998
- [j1]Gal Chechik, Isaac Meilijson, Eytan Ruppin:
Synaptic Pruning In Development: A Computational Account. Neural Comput. 10(7): 1759-1777 (1998) - [c1]Gal Chechik, Isaac Meilijson, Eytan Ruppin:
Neuronal Regulation Implements Efficient Synaptic Pruning. NIPS 1998: 97-103
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-07-22 20:26 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
