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ORCIDZhangyang Wang
Zhangyang (Atlas) Wang – Zhang-Yang Wang
Person information
- affiliation: University of Texas at Austin, Cockrell School of Engineering, TX, USA
- affiliation (former): Texas A&M University, College Station, TX, USA
- affiliation (PhD 2016): University of Illinois Urbana-Champaign, Urbana, IL, USA
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2020 – today
- 2023
[j52]Sina Mohseni
, Haotao Wang, Chaowei Xiao, Zhiding Yu, Zhangyang Wang, Jay Yadawa:
Taxonomy of Machine Learning Safety: A Survey and Primer. ACM Comput. Surv. 55(8): 157:1-157:38 (2023)- [j51]Wenqing Zheng, Hao (Frank) Yang, Jiarui Cai, Peihao Wang, Xuan Jiang, Simon Shaolei Du, Yinhai Wang, Zhangyang Wang:
Integrating the traffic science with representation learning for city-wide network congestion prediction. Inf. Fusion 99: 101837 (2023) - [j50]Haotao Wang, Tianlong Chen, Zhangyang Wang, Kede Ma:
Troubleshooting image segmentation models with human-in-the-loop. Mach. Learn. 112(3): 1033-1051 (2023) - [j49]Tianlong Chen, Kaixiong Zhou, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang:
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 2769-2781 (2023) - [j48]Priya Narayanan, Xin Hu, Zhenyu Wu, Matthew D. Thielke, John G. Rogers, Andre V. Harrison, John A. D'Agostino, James D. Brown, Long P. Quang, James R. Uplinger, Heesung Kwon, Zhangyang Wang:
A Multi-Purpose Realistic Haze Benchmark With Quantifiable Haze Levels and Ground Truth. IEEE Trans. Image Process. 32: 3481-3492 (2023) - [j47]Qiucheng Wu, Yifan Jiang, Junru Wu, Victor Kulikov, Vidit Goel, Nikita Orlov, Humphrey Shi, Zhangyang Wang, Shiyu Chang:
Broad Spectrum Image Deblurring via an Adaptive Super-Network. IEEE Trans. Image Process. 32: 5270-5282 (2023) - [j46]Yan Han, Gregory Holste, Ying Ding, Ahmed H. Tewfik, Yifan Peng, Zhangyang Wang:
Radiomics-Guided Global-Local Transformer for Weakly Supervised Pathology Localization in Chest X-Rays. IEEE Trans. Medical Imaging 42(3): 750-761 (2023) - [j45]Zhangheng Li, Tianlong Chen, Linyi Li, Bo Li, Zhangyang Wang:
Can Pruning Improve Certified Robustness of Neural Networks? Trans. Mach. Learn. Res. 2023 (2023) - [j44]Haotao Wang, Junyuan Hong, Jiayu Zhou, Zhangyang Wang:
How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shifts. Trans. Mach. Learn. Res. 2023 (2023) - [j43]Xiaohan Chen, Yang Zhao, Yue Wang, Pengfei Xu, Haoran You, Chaojian Li, Yonggan Fu, Yingyan Lin, Zhangyang Wang:
SmartDeal: Remodeling Deep Network Weights for Efficient Inference and Training. IEEE Trans. Neural Networks Learn. Syst. 34(10): 7099-7113 (2023) - [c256]Howard Heaton, Xiaohan Chen, Zhangyang Wang, Wotao Yin:
Safeguarded Learned Convex Optimization. AAAI 2023: 7848-7855 - [c255]Junyuan Hong, Haotao Wang, Zhangyang Wang, Jiayu Zhou:
Federated Robustness Propagation: Sharing Adversarial Robustness in Heterogeneous Federated Learning. AAAI 2023: 7893-7901 - [c254]Zhenglun Kong, Haoyu Ma, Geng Yuan, Mengshu Sun, Yanyue Xie, Peiyan Dong, Xin Meng, Xuan Shen, Hao Tang, Minghai Qin, Tianlong Chen, Xiaolong Ma, Xiaohui Xie, Zhangyang Wang, Yanzhi Wang:
Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training. AAAI 2023: 8360-8368 - [c253]Xuxi Chen, Tianlong Chen, Weizhu Chen, Ahmed Hassan Awadallah, Zhangyang Wang, Yu Cheng:
DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models. ACL (1) 2023: 8208-8222 - [c252]Hongru Yang, Zhangyang Wang:
On the Neural Tangent Kernel Analysis of Randomly Pruned Neural Networks. AISTATS 2023: 1513-1553 - [c251]Junjie Yang, Tianlong Chen, Mingkang Zhu, Fengxiang He, Dacheng Tao, Yingbin Liang, Zhangyang Wang:
Learning to Generalize Provably in Learning to Optimize. AISTATS 2023: 9807-9825 - [c250]Yimeng Zhang, Akshay Karkal Kamath, Qiucheng Wu, Zhiwen Fan, Wuyang Chen, Zhangyang Wang, Shiyu Chang, Sijia Liu, Cong Hao:
Data-Model-Circuit Tri-Design for Ultra-Light Video Intelligence on Edge Devices. ASP-DAC 2023: 745-750 - [c249]Yifan Jiang, Peter Hedman, Ben Mildenhall, Dejia Xu, Jonathan T. Barron, Zhangyang Wang, Tianfan Xue:
AligNeRF: High-Fidelity Neural Radiance Fields via Alignment-Aware Training. CVPR 2023: 46-55 - [c248]Wentao Zhu, Yufang Huang, Xiufeng Xie, Wenxian Liu, Jincan Deng, Debing Zhang, Zhangyang Wang, Ji Liu:
AutoShot: A Short Video Dataset and State-of-the-Art Shot Boundary Detection. CVPR Workshops 2023: 2238-2247 - [c247]Dejia Xu, Yifan Jiang, Peihao Wang, Zhiwen Fan, Yi Wang, Zhangyang Wang:
NeuralLift-360: Lifting an in-the-Wild 2D Photo to A 3D Object with 360° Views. CVPR 2023: 4479-4489 - [c246]Zhangheng Li, Yu Gong, Zhenyu Zhang, Xingyun Xue, Tianlong Chen, Yi Liang, Bo Yuan, Zhangyang Wang:
Accelerable Lottery Tickets with the Mixed-Precision Quantization. CVPR Workshops 2023: 4604-4612 - [c245]Ruisi Cai, Xiaohan Chen, Shiwei Liu, Jayanth Srinivasa, Myungjin Lee, Ramana Kompella, Zhangyang Wang:
Many-Task Federated Learning: A New Problem Setting and A Simple Baseline. CVPR Workshops 2023: 5037-5045 - [c244]Xinyu Gong, Sreyas Mohan, Naina Dhingra, Jean-Charles Bazin, Yilei Li, Zhangyang Wang, Rakesh Ranjan:
MMG-Ego4D: Multi-Modal Generalization in Egocentric Action Recognition. CVPR 2023: 6481-6491 - [c243]Haoming Lu, Hazarapet Tunanyan, Kai Wang, Shant Navasardyan, Zhangyang Wang, Humphrey Shi:
Specialist Diffusion: Plug-and-Play Sample-Efficient Fine-Tuning of Text-to-Image Diffusion Models to Learn Any Unseen Style. CVPR 2023: 14267-14276 - [c242]Tianlong Chen, Chengyue Gong, Daniel Jesus Diaz, Xuxi Chen, Jordan Tyler Wells, Qiang Liu, Zhangyang Wang, Andrew D. Ellington, Alex Dimakis, Adam R. Klivans:
HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing. ICLR 2023 - [c241]Tianlong Chen, Zhenyu Zhang, Ajay Kumar Jaiswal, Shiwei Liu, Zhangyang Wang:
Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers. ICLR 2023 - [c240]Zhiwen Fan, Peihao Wang, Yifan Jiang, Xinyu Gong, Dejia Xu, Zhangyang Wang:
NeRF-SOS: Any-View Self-supervised Object Segmentation on Complex Scenes. ICLR 2023 - [c239]Hehe Fan, Zhangyang Wang, Yi Yang, Mohan S. Kankanhalli:
Continuous-Discrete Convolution for Geometry-Sequence Modeling in Proteins. ICLR 2023 - [c238]Duc N. M. Hoang, Shiwei Liu, Radu Marculescu, Zhangyang Wang:
Revisiting Pruning at Initialization Through the Lens of Ramanujan Graph. ICLR 2023 - [c237]Ziyu Jiang, Yinpeng Chen, Mengchen Liu, Dongdong Chen, Xiyang Dai, Lu Yuan, Zicheng Liu, Zhangyang Wang:
Layer Grafted Pre-training: Bridging Contrastive Learning And Masked Image Modeling For Label-Efficient Representations. ICLR 2023 - [c236]Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao, Boqian Wu, Tommi Kärkkäinen, Mykola Pechenizkiy, Decebal Constantin Mocanu, Zhangyang Wang:
More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity. ICLR 2023 - [c235]Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Kumar Jaiswal, Zhangyang Wang:
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! ICLR 2023 - [c234]Mukund Varma T, Peihao Wang, Xuxi Chen, Tianlong Chen, Subhashini Venugopalan, Zhangyang Wang:
Is Attention All That NeRF Needs? ICLR 2023 - [c233]Peihao Wang, Rameswar Panda, Lucas Torroba Hennigen, Philip Greengard, Leonid Karlinsky, Rogério Feris, David Daniel Cox, Zhangyang Wang, Yoon Kim:
Learning to Grow Pretrained Models for Efficient Transformer Training. ICLR 2023 - [c232]Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li:
Equivariant Hypergraph Diffusion Neural Operators. ICLR 2023 - [c231]Junjie Yang, Xuxi Chen, Tianlong Chen, Zhangyang Wang, Yingbin Liang:
M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation. ICLR 2023 - [c230]Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen:
Graph Domain Adaptation via Theory-Grounded Spectral Regularization. ICLR 2023 - [c229]Shuyang Yu, Junyuan Hong, Haotao Wang, Zhangyang Wang, Jiayu Zhou:
Turning the Curse of Heterogeneity in Federated Learning into a Blessing for Out-of-Distribution Detection. ICLR 2023 - [c228]Ruisi Cai, Zhenyu Zhang, Zhangyang Wang:
Robust Weight Signatures: Gaining Robustness as Easy as Patching Weights? ICML 2023: 3495-3506 - [c227]Xuxi Chen, Nelson Vadori, Tianlong Chen, Zhangyang Wang:
Learning to Optimize Differentiable Games. ICML 2023: 5036-5051 - [c226]Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu:
Are Large Kernels Better Teachers than Transformers for ConvNets? ICML 2023: 14023-14038 - [c225]Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang:
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication. ICML 2023: 14679-14690 - [c224]Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang:
Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models. ICML 2023: 14691-14701 - [c223]Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin, HanQin Cai:
Towards Constituting Mathematical Structures for Learning to Optimize. ICML 2023: 21426-21449 - [c222]Yeonju Ro, Zhangyang Wang, Vijay Chidambaram, Aditya Akella:
Lowering the Pre-training Tax for Gradient-based Subset Training: A Lightweight Distributed Pre-Training Toolkit. ICML 2023: 29130-29142 - [c221]Peihao Wang, Rameswar Panda, Zhangyang Wang:
Data Efficient Neural Scaling Law via Model Reusing. ICML 2023: 36193-36204 - [c220]Wenqing Zheng, S. P. Sharan, Ajay Kumar Jaiswal, Kevin Wang, Yihan Xi, Dejia Xu, Zhangyang Wang:
Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation. ICML 2023: 42403-42419 - [c219]Gregory Holste, Ziyu Jiang, Ajay Jaiswal, Maria Hanna, Shlomo Minkowitz, Alan C. Legasto, Joanna G. Escalon, Sharon Steinberger, Mark Bittman, Thomas C. Shen, Ying Ding, Ronald M. Summers, George Shih, Yifan Peng, Zhangyang Wang:
How Does Pruning Impact Long-Tailed Multi-label Medical Image Classifiers? MICCAI (5) 2023: 663-673 - [c218]Ajay Jaiswal, Tianlong Chen, Justin F. Rousseau, Yifan Peng, Ying Ding, Zhangyang Wang:
Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances. WACV 2023: 4976-4985 - [c217]Yan Han, Edward W. Huang, Wenqing Zheng, Nikhil Rao, Zhangyang Wang, Karthik Subbian:
Search Behavior Prediction: A Hypergraph Perspective. WSDM 2023: 697-705 - [i279]Hongru Yang, Ziyu Jiang, Ruizhe Zhang, Zhangyang Wang, Yingbin Liang:
Convergence and Generalization of Wide Neural Networks with Large Bias. CoRR abs/2301.00327 (2023) - [i278]Hongru Yang, Yingbin Liang, Xiaojie Guo, Lingfei Wu, Zhangyang Wang:
Pruning Before Training May Improve Generalization, Provably. CoRR abs/2301.00335 (2023) - [i277]Mingquan Lin, Yuyun Xiao, Bo-Jian Hou, Tingyi Wanyan, Mohit Manoj Sharma, Zhangyang Wang, Fei Wang, Sarah Van Tassel, Yifan Peng:
Evaluate underdiagnosis and overdiagnosis bias of deep learning model on primary open-angle glaucoma diagnosis in under-served patient populations. CoRR abs/2301.11315 (2023) - [i276]Shiwei Liu, Zhangyang Wang:
Ten Lessons We Have Learned in the New "Sparseland": A Short Handbook for Sparse Neural Network Researchers. CoRR abs/2302.02596 (2023) - [i275]Junjie Yang, Tianlong Chen, Mingkang Zhu, Fengxiang He, Dacheng Tao, Yingbin Liang, Zhangyang Wang:
Learning to Generalize Provably in Learning to Optimize. CoRR abs/2302.11085 (2023) - [i274]Ruisi Cai, Zhenyu Zhang, Zhangyang Wang:
Robust Weight Signatures: Gaining Robustness as Easy as Patching Weights? CoRR abs/2302.12480 (2023) - [i273]Ziyu Jiang, Yinpeng Chen, Mengchen Liu, Dongdong Chen, Xiyang Dai, Lu Yuan, Zicheng Liu, Zhangyang Wang:
Layer Grafted Pre-training: Bridging Contrastive Learning And Masked Image Modeling For Label-Efficient Representations. CoRR abs/2302.14138 (2023) - [i272]Wenqing Zheng, Edward W. Huang, Nikhil Rao, Zhangyang Wang, Karthik Subbian:
You Only Transfer What You Share: Intersection-Induced Graph Transfer Learning for Link Prediction. CoRR abs/2302.14189 (2023) - [i271]Junjie Yang, Xuxi Chen, Tianlong Chen, Zhangyang Wang, Yingbin Liang:
M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation. CoRR abs/2303.00039 (2023) - [i270]Peihao Wang, Rameswar Panda, Lucas Torroba Hennigen, Philip Greengard, Leonid Karlinsky, Rogério Feris, David Daniel Cox, Zhangyang Wang, Yoon Kim:
Learning to Grow Pretrained Models for Efficient Transformer Training. CoRR abs/2303.00980 (2023) - [i269]Tianlong Chen, Zhenyu Zhang, Ajay Jaiswal, Shiwei Liu, Zhangyang Wang:
Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers. CoRR abs/2303.01610 (2023) - [i268]Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Jaiswal, Zhangyang Wang:
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! CoRR abs/2303.02141 (2023) - [i267]Levon Khachatryan, Andranik Movsisyan, Vahram Tadevosyan, Roberto Henschel, Zhangyang Wang, Shant Navasardyan, Humphrey Shi:
Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators. CoRR abs/2303.13439 (2023) - [i266]Vidit Goel, Elia Peruzzo, Yifan Jiang, Dejia Xu, Nicu Sebe, Trevor Darrell, Zhangyang Wang, Humphrey Shi:
PAIR-Diffusion: Object-Level Image Editing with Structure-and-Appearance Paired Diffusion Models. CoRR abs/2303.17546 (2023) - [i265]Eric Zhang, Kai Wang, Xingqian Xu, Zhangyang Wang, Humphrey Shi:
Forget-Me-Not: Learning to Forget in Text-to-Image Diffusion Models. CoRR abs/2303.17591 (2023) - [i264]Haotao Wang, Ziyu Jiang, Yan Han, Zhangyang Wang:
Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling. CoRR abs/2304.02806 (2023) - [i263]Wentao Zhu, Yufang Huang, Xiufeng Xie, Wenxian Liu, Jincan Deng, Debing Zhang, Zhangyang Wang, Ji Liu:
AutoShot: A Short Video Dataset and State-of-the-Art Shot Boundary Detection. CoRR abs/2304.06116 (2023) - [i262]Zhendong Wang, Yifan Jiang, Huangjie Zheng, Peihao Wang, Pengcheng He, Zhangyang Wang, Weizhu Chen, Mingyuan Zhou:
Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models. CoRR abs/2304.12526 (2023) - [i261]Zehao Wang, Long-Kun Shan, Tong-Tian Weng, Tian-Long Chen, Qi-Yu Wang, Xiang-Dong Chen, Zhang-Yang Wang, Guang-Can Guo, Fang-Wen Sun:
Learning imaging mechanism directly from optical microscopy observations. CoRR abs/2304.12584 (2023) - [i260]Wenqing Zheng, S. P. Sharan, Ajay Kumar Jaiswal, Kevin Wang, Yihan Xi, Dejia Xu, Zhangyang Wang:
Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generation. CoRR abs/2305.00909 (2023) - [i259]Zhendong Wang, Yifan Jiang, Yadong Lu, Yelong Shen, Pengcheng He, Weizhu Chen, Zhangyang Wang, Mingyuan Zhou:
In-Context Learning Unlocked for Diffusion Models. CoRR abs/2305.01115 (2023) - [i258]Xinyu Gong, Sreyas Mohan, Naina Dhingra, Jean-Charles Bazin, Yilei Li, Zhangyang Wang, Rakesh Ranjan:
MMG-Ego4D: Multi-Modal Generalization in Egocentric Action Recognition. CoRR abs/2305.07214 (2023) - [i257]Zhiwen Fan, Panwang Pan, Peihao Wang, Yifan Jiang, Dejia Xu, Hanwen Jiang, Zhangyang Wang:
POPE: 6-DoF Promptable Pose Estimation of Any Object, in Any Scene, with One Reference. CoRR abs/2305.15727 (2023) - [i256]Xingqian Xu, Jiayi Guo, Zhangyang Wang, Gao Huang, Irfan Essa, Humphrey Shi:
Prompt-Free Diffusion: Taking "Text" out of Text-to-Image Diffusion Models. CoRR abs/2305.16223 (2023) - [i255]Jialin Liu, Xiaohan Chen, Zhangyang Wang, Wotao Yin, HanQin Cai:
Towards Constituting Mathematical Structures for Learning to Optimize. CoRR abs/2305.18577 (2023) - [i254]Rishov Sarkar, Hanxue Liang, Zhiwen Fan, Zhangyang Wang, Cong Hao:
Edge-MoE: Memory-Efficient Multi-Task Vision Transformer Architecture with Task-level Sparsity via Mixture-of-Experts. CoRR abs/2305.18691 (2023) - [i253]Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu:
Are Large Kernels Better Teachers than Transformers for ConvNets? CoRR abs/2305.19412 (2023) - [i252]Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu:
Dynamic Sparsity Is Channel-Level Sparsity Learner. CoRR abs/2305.19454 (2023) - [i251]Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Zhangyang Wang:
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter. CoRR abs/2306.03805 (2023) - [i250]Panwang Pan, Zhiwen Fan, Brandon Y. Feng, Peihao Wang, Chenxin Li, Zhangyang Wang:
Learning to Estimate 6DoF Pose from Limited Data: A Few-Shot, Generalizable Approach using RGB Images. CoRR abs/2306.07598 (2023) - [i249]Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang:
Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models. CoRR abs/2306.10460 (2023) - [i248]Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang:
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication. CoRR abs/2306.10466 (2023) - [i247]Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark W. Barrett, Zhangyang Wang, Beidi Chen:
H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. CoRR abs/2306.14048 (2023) - [i246]Feng Liu, Ryan Ashbaugh, Nicholas Chimitt, Najmul Hassan, Ali Hassani, Ajay Jaiswal, Minchul Kim, Zhiyuan Mao, Christopher Perry, Zhiyuan Ren, Yiyang Su, Pegah Varghaei, Kai Wang, Xingguang Zhang, Stanley H. Chan, Arun Ross, Humphrey Shi, Zhangyang Wang, Anil K. Jain, Xiaoming Liu:
FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude. CoRR abs/2306.17206 (2023) - [i245]Guihong Li, Duc Hoang, Kartikeya Bhardwaj, Ming Lin, Zhangyang Wang, Radu Marculescu:
Zero-Shot Neural Architecture Search: Challenges, Solutions, and Opportunities. CoRR abs/2307.01998 (2023) - [i244]Peihao Wang, Shenghao Yang, Shu Li, Zhangyang Wang, Pan Li:
Polynomial Width is Sufficient for Set Representation with High-dimensional Features. CoRR abs/2307.04001 (2023) - [i243]Dejia Xu, Xingqian Xu, Wenyan Cong, Humphrey Shi, Zhangyang Wang:
Reference-based Painterly Inpainting via Diffusion: Crossing the Wild Reference Domain Gap. CoRR abs/2307.10584 (2023) - [i242]Ajay Jaiswal, Xingguang Zhang, Stanley H. Chan, Zhangyang Wang:
Physics-Driven Turbulence Image Restoration with Stochastic Refinement. CoRR abs/2307.10603 (2023) - [i241]Daouda Sow, Sen Lin, Zhangyang Wang, Yingbin Liang:
Doubly Robust Instance-Reweighted Adversarial Training. CoRR abs/2308.00311 (2023) - [i240]Stefan Abi-Karam, Rishov Sarkar, Dejia Xu, Zhiwen Fan, Zhangyang Wang, Cong Hao:
INR-Arch: A Dataflow Architecture and Compiler for Arbitrary-Order Gradient Computations in Implicit Neural Representation Processing. CoRR abs/2308.05930 (2023) - [i239]Gregory Holste, Ziyu Jiang, Ajay Jaiswal, Maria Hanna, Shlomo Minkowitz, Alan C. Legasto, Joanna G. Escalon, Sharon Steinberger, Mark Bittman, Thomas C. Shen, Ying Ding, Ronald M. Summers, George Shih, Yifan Peng, Zhangyang Wang:
How Does Pruning Impact Long-Tailed Multi-Label Medical Image Classifiers? CoRR abs/2308.09180 (2023) - [i238]Yihua Zhang, Ruisi Cai, Tianlong Chen, Guanhua Zhang, Huan Zhang, Pin-Yu Chen, Shiyu Chang, Zhangyang Wang, Sijia Liu:
Robust Mixture-of-Expert Training for Convolutional Neural Networks. CoRR abs/2308.10110 (2023) - [i237]Wenyan Cong, Hanxue Liang, Peihao Wang, Zhiwen Fan, Tianlong Chen, Mukund Varma T, Yi Wang, Zhangyang Wang:
Enhancing NeRF akin to Enhancing LLMs: Generalizable NeRF Transformer with Mixture-of-View-Experts. CoRR abs/2308.11793 (2023) - [i236]Shuyang Yu, Junyuan Hong, Haobo Zhang, Haotao Wang, Zhangyang Wang, Jiayu Zhou:
Safe and Robust Watermark Injection with a Single OoD Image. CoRR abs/2309.01786 (2023) - [i235]Duc N. M. Hoang, Minsik Cho, Thomas Merth, Mohammad Rastegari, Zhangyang Wang:
(Dynamic) Prompting might be all you need to repair Compressed LLMs. CoRR abs/2310.00867 (2023) - [i234]Ajay Jaiswal, Zhe Gan, Xianzhi Du, Bowen Zhang, Zhangyang Wang, Yinfei Yang:
Compressing LLMs: The Truth is Rarely Pure and Never Simple. CoRR abs/2310.01382 (2023) - [i233]Lu Yin, Shiwei Liu, Ajay Jaiswal, Souvik Kundu, Zhangyang Wang:
Junk DNA Hypothesis: A Task-Centric Angle of LLM Pre-trained Weights through Sparsity. CoRR abs/2310.02277 (2023) - [i232]Yifan Jiang, Hao Tang, Jen-Hao Rick Chang, Liangchen Song, Zhangyang Wang, Liangliang Cao:
Efficient-3DiM: Learning a Generalizable Single-image Novel-view Synthesizer in One Day. CoRR abs/2310.03015 (2023) - [i231]Zhiwen Fan, Panwang Pan, Peihao Wang, Yifan Jiang, Hanwen Jiang, Dejia Xu, Zehao Zhu, Dilin Wang, Zhangyang Wang:
Drag View: Generalizable Novel View Synthesis with Unposed Imagery. CoRR abs/2310.03704 (2023) - [i230]Lu Yin, You Wu, Zhenyu Zhang, Cheng-Yu Hsieh, Yaqing Wang, Yiling Jia, Mykola Pechenizkiy, Yi Liang, Zhangyang Wang, Shiwei Liu:
Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. CoRR abs/2310.05175 (2023) - [i229]Xuxi Chen, Yu Yang, Zhangyang Wang, Baharan Mirzasoleiman:
Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality. CoRR abs/2310.06982 (2023) - [i228]Hazarapet Tunanyan, Dejia Xu, Shant Navasardyan, Zhangyang Wang, Humphrey Shi:
Multi-Concept T2I-Zero: Tweaking Only The Text Embeddings and Nothing Else. CoRR abs/2310.07419 (2023) - [i227]Gregory Holste, Yiliang Zhou, Song Wang, Ajay Jaiswal, Mingquan Lin, Sherry Zhuge, Yuzhe Yang, Dongkyun Kim, Trong-Hieu Nguyen Mau, Minh-Triet Tran, Jaehyup Jeong, Wongi Park, Jongbin Ryu, Feng Hong, Arsh Verma, Yosuke Yamagishi, Changhyun Kim, Hyeryeong Seo, Myungjoo Kang, Leo Anthony Celi, Zhiyong Lu, Ronald M. Summers, George Shih, Zhangyang Wang, Yifan Peng:
Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge. CoRR abs/2310.16112 (2023) - [i226]Yunhao Yang, Neel P. Bhatt, Tyler Ingebrand, William Ward, Steven Carr, Zhangyang Wang, Ufuk Topcu:
Fine-Tuning Language Models Using Formal Methods Feedback. CoRR abs/2310.18239 (2023) - [i225]Zhiwen Fan, Kevin Wang, Kairun Wen, Zehao Zhu, Dejia Xu, Zhangyang Wang:
LightGaussian: Unbounded 3D Gaussian Compression with 15x Reduction and 200+ FPS. CoRR abs/2311.17245 (2023) - 2022
- [j42]Tianlong Chen, Xiaohan Chen, Wuyang Chen, Howard Heaton, Jialin Liu, Zhangyang Wang, Wotao Yin:
Learning to Optimize: A Primer and A Benchmark. J. Mach. Learn. Res. 23: 189:1-189:59 (2022) - [j41]Zhenyu Wu, Haotao Wang, Zhaowen Wang, Hailin Jin, Zhangyang Wang:
Privacy-Preserving Deep Action Recognition: An Adversarial Learning Framework and A New Dataset. IEEE Trans. Pattern Anal. Mach. Intell. 44(4): 2126-2139 (2022) - [j40]