Greg Yang

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 50

Top Topics

Top Venues

Publications

Greg Yang, Dingli Yu, Chen Zhu, Soufiane Hayou
Tensor Programs VI: Feature Learning in Infinite Depth Neural Networks. ICLR (2024)
Greg Yang, Dingli Yu, Chen Zhu, Soufiane Hayou
Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks. CoRR (2023)
Greg Yang, Etai Littwin
Tensor Programs IVb: Adaptive Optimization in the Infinite-Width Limit. CoRR (2023)
Soufiane Hayou, Greg Yang
Width and Depth Limits Commute in Residual Networks. CoRR (2023)
Greg Yang, James B. Simon, Jeremy Bernstein
A Spectral Condition for Feature Learning. CoRR (2023)
Soufiane Hayou, Greg Yang
Width and Depth Limits Commute in Residual Networks. ICML (2023)
Etai Littwin, Greg Yang
Adaptive Optimization in the ∞-Width Limit. ICLR (2023)
Greg Yang, Edward J. Hu, Igor Babuschkin, Szymon Sidor, Xiaodong Liu, David Farhi, Nick Ryder, Jakub Pachocki, Weizhu Chen, Jianfeng Gao
Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer. CoRR (2022)
Eugene Golikov, Greg Yang
Non-Gaussian Tensor Programs. NeurIPS (2022)
Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Yuanqing Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry
3DB: A Framework for Debugging Computer Vision Models. NeurIPS (2022)
Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Zhichao Wang, Denny Wu, Greg Yang
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation. NeurIPS (2022)
Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Zhichao Wang, Denny Wu, Greg Yang
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation. CoRR (2022)
Greg Yang, Michael Santacroce, Edward J. Hu
Efficient Computation of Deep Nonlinear Infinite-Width Neural Networks that Learn Features. ICLR (2022)
Greg Yang, Etai Littwin
Tensor Programs IIb: Architectural Universality of Neural Tangent Kernel Training Dynamics. CoRR (2021)
Greg Yang, Edward J. Hu
Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks. ICML (2021)
Greg Yang, Etai Littwin
Tensor Programs IIb: Architectural Universality Of Neural Tangent Kernel Training Dynamics. ICML (2021)
Etai Littwin, Omid Saremi, Shuangfei Zhai, Vimal Thilak, Hanlin Goh, Joshua M. Susskind, Greg Yang
Implicit Acceleration and Feature Learning in Infinitely Wide Neural Networks with Bottlenecks. CoRR (2021)
Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Yuanqing Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry
3DB: A Framework for Debugging Computer Vision Models. CoRR (2021)
Subhabrata Mukherjee, Xiaodong Liu, Guoqing Zheng, Saghar Hosseini, Hao Cheng, Greg Yang, Christopher Meek, Ahmed Hassan Awadallah, Jianfeng Gao
CLUES: Few-Shot Learning Evaluation in Natural Language Understanding. CoRR (2021)
Greg Yang
Tensor Programs III: Neural Matrix Laws. CoRR (2020)
Hadi Salman, Mingjie Sun, Greg Yang, Ashish Kapoor, J. Zico Kolter
Denoised Smoothing: A Provable Defense for Pretrained Classifiers. NeurIPS (2020)
Justin Chen, Christopher Eur, Greg Yang, Mengyuan Zhang
Free resolutions of function classes via order complexes. Adv. Appl. Math. 120 (2020)
Hadi Salman, Mingjie Sun, Greg Yang, Ashish Kapoor, J. Zico Kolter
Black-box Smoothing: A Provable Defense for Pretrained Classifiers. CoRR (2020)
Etai Littwin, Tomer Galanti, Lior Wolf, Greg Yang
On Infinite-Width Hypernetworks. NeurIPS (2020)
Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya P. Razenshteyn, Jerry Li
Randomized Smoothing of All Shapes and Sizes. CoRR (2020)
Greg Yang
Tensor Programs II: Neural Tangent Kernel for Any Architecture. CoRR (2020)
Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya P. Razenshteyn, Jerry Li
Randomized Smoothing of All Shapes and Sizes. ICML (2020)
Greg Yang, J. Edward Hu
Feature Learning in Infinite-Width Neural Networks. CoRR (2020)
J. Edward Hu, Adith Swaminathan, Hadi Salman, Greg Yang
Improved Image Wasserstein Attacks and Defenses. CoRR (2020)
Roman Novak, Lechao Xiao, Yasaman Bahri, Jaehoon Lee, Greg Yang, Jiri Hron, Daniel A. Abolafia, Jeffrey Pennington, Jascha Sohl-Dickstein
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes. ICLR (Poster) (2019)
Hadi Salman, Greg Yang, Huan Zhang, Cho-Jui Hsieh, Pengchuan Zhang
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks. CoRR (2019)
Hadi Salman, Jerry Li, Ilya P. Razenshteyn, Pengchuan Zhang, Huan Zhang, Sébastien Bubeck, Greg Yang
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers. NeurIPS (2019)
Greg Yang
Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes. CoRR (2019)
Greg Yang
Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes. NeurIPS (2019)
Justin Chen, Christopher Eur, Greg Yang, Mengyuan Zhang
Free resolutions of function classes via order complexes. CoRR (2019)
Greg Yang
Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel Derivation. CoRR (2019)
Dar Gilboa, Bo Chang, Minmin Chen, Greg Yang, Samuel S. Schoenholz, Ed H. Chi, Jeffrey Pennington
Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs. CoRR (2019)
Greg Yang, Hadi Salman
A Fine-Grained Spectral Perspective on Neural Networks. CoRR (2019)
Greg Yang, Jeffrey Pennington, Vinay Rao, Jascha Sohl-Dickstein, Samuel S. Schoenholz
A Mean Field Theory of Batch Normalization. ICLR (Poster) (2019)
Hadi Salman, Greg Yang, Jerry Li, Pengchuan Zhang, Huan Zhang, Ilya P. Razenshteyn, Sébastien Bubeck
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers. CoRR (2019)
Greg Yang, Jeffrey Pennington, Vinay Rao, Jascha Sohl-Dickstein, Samuel S. Schoenholz
A Mean Field Theory of Batch Normalization. CoRR (2019)
Matthew J. Hausknecht, Ricky Loynd, Greg Yang, Adith Swaminathan, Jason D. Williams
NAIL: A General Interactive Fiction Agent. CoRR (2019)
Hadi Salman, Greg Yang, Huan Zhang, Cho-Jui Hsieh, Pengchuan Zhang
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks. NeurIPS (2019)
Greg Yang
A Homological Theory of Functions: Nonuniform Boolean Complexity Separation and VC Dimension Bound Via Algebraic Topology, and a Homological Farkas Lemma. ITCS (2018)
Greg Yang, Alexander M. Rush
Lie-Access Neural Turing Machines. ICLR (Poster) (2017)
Greg Yang
A Homological Theory of Functions. CoRR (2017)
Greg Yang, Samuel S. Schoenholz
Mean Field Residual Networks: On the Edge of Chaos. NIPS (2017)
Greg Yang, Samuel S. Schoenholz
Mean Field Residual Networks: On the Edge of Chaos. CoRR (2017)
Greg Yang
Lie Access Neural Turing Machine. CoRR (2016)
Greg Yang, Alexander M. Rush
Lie-Access Neural Turing Machines. CoRR (2016)
Greg Yang
Computability of validity and satisfiability in probability logics over finite and countable models. J. Appl. Non Class. Logics 25 (4) (2015)
Greg Yang
Computabilities of Validity and Satisfiability in Probability Logics over Finite and Countable Models. CoRR (2014)