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ORCIDTomer Galanti
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2020 – today
- 2024
[i25]Nadav Timor, Jonathan Mamou, Daniel Korat, Moshe Berchansky, Oren Pereg, Moshe Wasserblat, Tomer Galanti, Michal Gordon, David Harel:
Distributed Speculative Inference of Large Language Models. CoRR abs/2405.14105 (2024)- [i24]Yulu Gan, Tomer Galanti, Tomaso A. Poggio, Eran Malach:
On the Power of Decision Trees in Auto-Regressive Language Modeling. CoRR abs/2409.19150 (2024) - 2023
- [j4]Ido Ben-Shaul, Tomer Galanti, Shai Dekel:
Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions. Trans. Mach. Learn. Res. 2023 (2023) - [j3]Tomer Galanti, Liane Galanti, Ido Ben-Shaul:
Comparative Generalization Bounds for Deep Neural Networks. Trans. Mach. Learn. Res. 2023 (2023) - [c16]Akshay Rangamani, Marius Lindegaard, Tomer Galanti, Tomaso A. Poggio:
Feature learning in deep classifiers through Intermediate Neural Collapse. ICML 2023: 28729-28745 - [c15]Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti, Shai Dekel, Yann LeCun:
Reverse Engineering Self-Supervised Learning. NeurIPS 2023 - [c14]Tomer Galanti, Mengjia Xu, Liane Galanti, Tomaso A. Poggio:
Norm-based Generalization Bounds for Sparse Neural Networks. NeurIPS 2023 - [i23]Ido Ben-Shaul, Tomer Galanti, Shai Dekel:
Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions. CoRR abs/2301.04605 (2023) - [i22]Tomer Galanti, Mengjia Xu, Liane Galanti, Tomaso A. Poggio:
Norm-based Generalization Bounds for Compositionally Sparse Neural Networks. CoRR abs/2301.12033 (2023) - [i21]Ziyin Liu, Botao Li, Tomer Galanti, Masahito Ueda:
The Probabilistic Stability of Stochastic Gradient Descent. CoRR abs/2303.13093 (2023) - [i20]Ido Ben-Shaul, Ravid Shwartz-Ziv, Tomer Galanti, Shai Dekel, Yann LeCun:
Reverse Engineering Self-Supervised Learning. CoRR abs/2305.15614 (2023) - [i19]Ameen Ali, Tomer Galanti, Lior Wolf:
Centered Self-Attention Layers. CoRR abs/2306.01610 (2023) - 2022
- [c13]Ameen Ali, Tomer Galanti, Evgenii Zheltonozhskii, Chaim Baskin, Lior Wolf:
Weakly Supervised Discovery of Semantic Attributes. CLeaR 2022: 44-69 - [c12]Chenfeng Xu
, Shijia Yang, Tomer Galanti, Bichen Wu, Xiangyu Yue, Bohan Zhai, Wei Zhan, Peter Vajda, Kurt Keutzer, Masayoshi Tomizuka:
Image2Point: 3D Point-Cloud Understanding with 2D Image Pretrained Models. ECCV (37) 2022: 638-656 - [c11]Tomer Galanti, András György, Marcus Hutter:
On the Role of Neural Collapse in Transfer Learning. ICLR 2022 - [i18]Tomer Galanti:
A Note on the Implicit Bias Towards Minimal Depth of Deep Neural Networks. CoRR abs/2202.09028 (2022) - [i17]Tomer Galanti, Tomaso A. Poggio:
SGD Noise and Implicit Low-Rank Bias in Deep Neural Networks. CoRR abs/2206.05794 (2022) - [i16]Tomer Galanti, András György, Marcus Hutter:
Generalization Bounds for Transfer Learning with Pretrained Classifiers. CoRR abs/2212.12532 (2022) - 2021
- [b1]Tomer Galanti:
On the Emergence of Semantic Structure in Deep Learning. Tel Aviv University, Israel, 2021 - [j2]Yaniv Benny, Tomer Galanti, Sagie Benaim, Lior Wolf:
Evaluation Metrics for Conditional Image Generation. Int. J. Comput. Vis. 129(5): 1712-1731 (2021) - [j1]Tomer Galanti, Sagie Benaim, Lior Wolf:
Risk Bounds for Unsupervised Cross-Domain Mapping with IPMs. J. Mach. Learn. Res. 22: 90:1-90:42 (2021) - [c10]Raphael Bensadoun, Shir Gur, Tomer Galanti, Lior Wolf:
Meta Internal Learning. NeurIPS 2021: 20645-20656 - [c9]Etai Littwin, Tomer Galanti, Lior Wolf:
On random kernels of residual architectures. UAI 2021: 897-907 - [i15]Ameen Ali, Tomer Galanti, Evgeniy Zheltonozhskiy, Chaim Baskin, Lior Wolf:
Intersection Regularization for Extracting Semantic Attributes. CoRR abs/2103.11888 (2021) - [i14]Raphael Bensadoun, Shir Gur, Tomer Galanti, Lior Wolf:
Meta Internal Learning. CoRR abs/2110.02900 (2021) - [i13]Tomer Galanti, András György, Marcus Hutter:
On the Role of Neural Collapse in Transfer Learning. CoRR abs/2112.15121 (2021) - 2020
- [c8]Tomer Galanti, Lior Wolf:
On the Modularity of Hypernetworks. NeurIPS 2020 - [c7]Etai Littwin, Tomer Galanti, Lior Wolf, Greg Yang:
On Infinite-Width Hypernetworks. NeurIPS 2020 - [i12]Ori Press, Tomer Galanti, Sagie Benaim, Lior Wolf:
Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer. CoRR abs/2001.05017 (2020) - [i11]Lior Wolf, Sagie Benaim, Tomer Galanti:
Unsupervised Learning of the Set of Local Maxima. CoRR abs/2001.05026 (2020) - [i10]Lior Wolf, Tomer Galanti, Tamir Hazan:
A Formal Approach to Explainability. CoRR abs/2001.05207 (2020) - [i9]Tomer Galanti, Lior Wolf:
Comparing the Parameter Complexity of Hypernetworks and the Embedding-Based Alternative. CoRR abs/2002.10006 (2020) - [i8]Tomer Galanti, Ofir Nabati, Lior Wolf:
A Critical View of the Structural Causal Model. CoRR abs/2002.10007 (2020) - [i7]Etai Littwin, Tomer Galanti, Lior Wolf:
On the Optimization Dynamics of Wide Hypernetworks. CoRR abs/2003.12193 (2020) - [i6]Yaniv Benny, Tomer Galanti, Sagie Benaim, Lior Wolf:
Evaluation Metrics for Conditional Image Generation. CoRR abs/2004.12361 (2020)
2010 – 2019
- 2019
- [c6]Lior Wolf, Tomer Galanti, Tamir Hazan:
A Formal Approach to Explainability. AIES 2019: 255-261 - [c5]Sagie Benaim, Michael Khaitov, Tomer Galanti, Lior Wolf:
Domain Intersection and Domain Difference. ICCV 2019: 3444-3452 - [c4]Ori Press, Tomer Galanti, Sagie Benaim, Lior Wolf:
Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer. ICLR (Poster) 2019 - [c3]Lior Wolf, Sagie Benaim, Tomer Galanti:
Unsupervised Learning of the Set of Local Maxima. ICLR (Poster) 2019 - [i5]Sagie Benaim, Michael Khaitov, Tomer Galanti, Lior Wolf:
Domain Intersection and Domain Difference. CoRR abs/1908.11628 (2019) - 2018
- [c2]Sagie Benaim, Tomer Galanti, Lior Wolf:
Estimating the Success of Unsupervised Image to Image Translation. ECCV (5) 2018: 222-238 - [c1]Tomer Galanti, Lior Wolf, Sagie Benaim:
The Role of Minimal Complexity Functions in Unsupervised Learning of Semantic Mappings. ICLR (Poster) 2018 - [i4]Tomer Galanti, Sagie Benaim, Lior Wolf:
Generalization Bounds for Unsupervised Cross-Domain Mapping with WGANs. CoRR abs/1807.08501 (2018) - 2017
- [i3]Tomer Galanti, Lior Wolf:
A Theory of Output-Side Unsupervised Domain Adaptation. CoRR abs/1703.01606 (2017) - [i2]Tomer Galanti, Lior Wolf:
Unsupervised Learning of Semantic Mappings. CoRR abs/1709.00074 (2017) - [i1]Sagie Benaim, Tomer Galanti, Lior Wolf:
Maximally Distant Cross Domain Generators for Estimating Per-Sample Error. CoRR abs/1712.07886 (2017)
Coauthor Index
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last updated on 2024-10-18 20:33 CEST by the dblp team
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