Greg Yang

According to our database, Greg Yang authored at least 40 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

A Spectral Condition for Feature Learning.

Greg Yang, James B. Simon, Jeremy Bernstein

CoRR, 2023

Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks.

Greg Yang, Dingli Yu, Chen Zhu, Soufiane Hayou

CoRR, 2023

Tensor Programs IVb: Adaptive Optimization in the Infinite-Width Limit.

Greg Yang, Etai Littwin

CoRR, 2023

Width and Depth Limits Commute in Residual Networks.

Soufiane Hayou, Greg Yang

Proceedings of the International Conference on Machine Learning, 2023

Adaptive Optimization in the ∞-Width Limit.

Etai Littwin, Greg Yang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer.

Greg Yang, Edward J. Hu, Igor Babuschkin, Szymon Sidor, Xiaodong Liu, David Farhi, Nick Ryder, Jakub Pachocki, Weizhu Chen, Jianfeng Gao

CoRR, 2022

3DB: A Framework for Debugging Computer Vision Models.

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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Non-Gaussian Tensor Programs.

Eugene Golikov, Greg Yang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation.

Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Zhichao Wang, Denny Wu, Greg Yang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Efficient Computation of Deep Nonlinear Infinite-Width Neural Networks that Learn Features.

Greg Yang, Michael Santacroce, Edward J. Hu

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

CLUES: Few-Shot Learning Evaluation in Natural Language Understanding.

Subhabrata Mukherjee, Xiaodong Liu, Guoqing Zheng, Saghar Hosseini, Hao Cheng, Greg Yang, Christopher Meek, Ahmed Hassan Awadallah, Jianfeng Gao

CoRR, 2021

Implicit Acceleration and Feature Learning in Infinitely Wide Neural Networks with Bottlenecks.

Etai Littwin, Omid Saremi, Shuangfei Zhai, Vimal Thilak, Hanlin Goh, Joshua M. Susskind, Greg Yang

CoRR, 2021

Tensor Programs IIb: Architectural Universality Of Neural Tangent Kernel Training Dynamics.

Greg Yang, Etai Littwin

Proceedings of the 38th International Conference on Machine Learning, 2021

Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks.

Greg Yang, Edward J. Hu

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Feature Learning in Infinite-Width Neural Networks.

Greg Yang, J. Edward Hu

CoRR, 2020

Tensor Programs III: Neural Matrix Laws.

Greg Yang

CoRR, 2020

Tensor Programs II: Neural Tangent Kernel for Any Architecture.

Greg Yang

CoRR, 2020

Improved Image Wasserstein Attacks and Defenses.

J. Edward Hu, Adith Swaminathan, Hadi Salman, Greg Yang

CoRR, 2020

Black-box Smoothing: A Provable Defense for Pretrained Classifiers.

Hadi Salman, Mingjie Sun, Greg Yang, Ashish Kapoor, J. Zico Kolter

CoRR, 2020

Free resolutions of function classes via order complexes.

Justin Chen, Christopher Eur, Greg Yang, Mengyuan Zhang

Adv. Appl. Math., 2020

Denoised Smoothing: A Provable Defense for Pretrained Classifiers.

Hadi Salman, Mingjie Sun, Greg Yang, Ashish Kapoor, J. Zico Kolter

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On Infinite-Width Hypernetworks.

Etai Littwin, Tomer Galanti, Lior Wolf, Greg Yang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Randomized Smoothing of All Shapes and Sizes.

Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya P. Razenshteyn, Jerry Li

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes.

Greg Yang

CoRR, 2019

A Fine-Grained Spectral Perspective on Neural Networks.

Greg Yang, Hadi Salman

CoRR, 2019

Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel Derivation.

Greg Yang

CoRR, 2019

NAIL: A General Interactive Fiction Agent.

Matthew J. Hausknecht, Ricky Loynd, Greg Yang, Adith Swaminathan, Jason D. Williams

CoRR, 2019

Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs.

Dar Gilboa, Bo Chang, Minmin Chen, Greg Yang, Samuel S. Schoenholz, Ed H. Chi, Jeffrey Pennington

CoRR, 2019

Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes.

Greg Yang

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks.

Hadi Salman, Greg Yang, Huan Zhang, Cho-Jui Hsieh, Pengchuan Zhang

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers.

Hadi Salman, Jerry Li, Ilya P. Razenshteyn, Pengchuan Zhang, Huan Zhang, Sébastien Bubeck, Greg Yang

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Mean Field Theory of Batch Normalization.

Greg Yang, Jeffrey Pennington, Vinay Rao, Jascha Sohl-Dickstein, Samuel S. Schoenholz

Proceedings of the 7th International Conference on Learning Representations, 2019

Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes.

Roman Novak, Lechao Xiao, Yasaman Bahri, Jaehoon Lee, Greg Yang, Jiri Hron, Daniel A. Abolafia, Jeffrey Pennington, Jascha Sohl-Dickstein

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

A Homological Theory of Functions: Nonuniform Boolean Complexity Separation and VC Dimension Bound Via Algebraic Topology, and a Homological Farkas Lemma.

Greg Yang

Proceedings of the 9th Innovations in Theoretical Computer Science Conference, 2018

2017

A Homological Theory of Functions.

Greg Yang

CoRR, 2017

Mean Field Residual Networks: On the Edge of Chaos.

Greg Yang, Samuel S. Schoenholz

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Lie-Access Neural Turing Machines.

Greg Yang, Alexander M. Rush

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Lie Access Neural Turing Machine.

Greg Yang

CoRR, 2016

2015

Computability of validity and satisfiability in probability logics over finite and countable models.

Greg Yang

J. Appl. Non Class. Logics, 2015

2014

Computabilities of Validity and Satisfiability in Probability Logics over Finite and Countable Models.

Greg Yang

CoRR, 2014