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Greg Yang
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2020 – today
- 2024
- [c20]Greg Yang, Dingli Yu, Chen Zhu, Soufiane Hayou:
Tensor Programs VI: Feature Learning in Infinite Depth Neural Networks. ICLR 2024 - 2023
- [c19]Etai Littwin, Greg Yang:
Adaptive Optimization in the ∞-Width Limit. ICLR 2023 - [c18]Soufiane Hayou, Greg Yang:
Width and Depth Limits Commute in Residual Networks. ICML 2023: 12700-12723 - [i30]Soufiane Hayou, Greg Yang:
Width and Depth Limits Commute in Residual Networks. CoRR abs/2302.00453 (2023) - [i29]Greg Yang, Etai Littwin:
Tensor Programs IVb: Adaptive Optimization in the Infinite-Width Limit. CoRR abs/2308.01814 (2023) - [i28]Greg Yang, Dingli Yu, Chen Zhu, Soufiane Hayou:
Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks. CoRR abs/2310.02244 (2023) - [i27]Greg Yang, James B. Simon, Jeremy Bernstein:
A Spectral Condition for Feature Learning. CoRR abs/2310.17813 (2023) - 2022
- [c17]Greg Yang, Michael Santacroce, Edward J. Hu:
Efficient Computation of Deep Nonlinear Infinite-Width Neural Networks that Learn Features. ICLR 2022 - [c16]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 - [c15]Eugene Golikov, Greg Yang:
Non-Gaussian Tensor Programs. NeurIPS 2022 - [c14]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 - [i26]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 abs/2203.03466 (2022) - [i25]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 abs/2205.01445 (2022) - 2021
- [c13]Greg Yang, Edward J. Hu:
Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks. ICML 2021: 11727-11737 - [c12]Greg Yang, Etai Littwin:
Tensor Programs IIb: Architectural Universality Of Neural Tangent Kernel Training Dynamics. ICML 2021: 11762-11772 - [i24]Greg Yang, Etai Littwin:
Tensor Programs IIb: Architectural Universality of Neural Tangent Kernel Training Dynamics. CoRR abs/2105.03703 (2021) - [i23]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 abs/2106.03805 (2021) - [i22]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 abs/2107.00364 (2021) - [i21]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 abs/2111.02570 (2021) - 2020
- [j2]Justin Chen, Christopher Eur, Greg Yang, Mengyuan Zhang:
Free resolutions of function classes via order complexes. Adv. Appl. Math. 120: 102074 (2020) - [c11]Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya P. Razenshteyn, Jerry Li:
Randomized Smoothing of All Shapes and Sizes. ICML 2020: 10693-10705 - [c10]Etai Littwin, Tomer Galanti, Lior Wolf, Greg Yang:
On Infinite-Width Hypernetworks. NeurIPS 2020 - [c9]Hadi Salman, Mingjie Sun, Greg Yang, Ashish Kapoor, J. Zico Kolter:
Denoised Smoothing: A Provable Defense for Pretrained Classifiers. NeurIPS 2020 - [i20]Greg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya P. Razenshteyn, Jerry Li:
Randomized Smoothing of All Shapes and Sizes. CoRR abs/2002.08118 (2020) - [i19]Hadi Salman, Mingjie Sun, Greg Yang, Ashish Kapoor, J. Zico Kolter:
Black-box Smoothing: A Provable Defense for Pretrained Classifiers. CoRR abs/2003.01908 (2020) - [i18]J. Edward Hu, Adith Swaminathan, Hadi Salman, Greg Yang:
Improved Image Wasserstein Attacks and Defenses. CoRR abs/2004.12478 (2020) - [i17]Greg Yang:
Tensor Programs II: Neural Tangent Kernel for Any Architecture. CoRR abs/2006.14548 (2020) - [i16]Greg Yang:
Tensor Programs III: Neural Matrix Laws. CoRR abs/2009.10685 (2020) - [i15]Greg Yang, J. Edward Hu:
Feature Learning in Infinite-Width Neural Networks. CoRR abs/2011.14522 (2020)
2010 – 2019
- 2019
- [c8]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 - [c7]Greg Yang, Jeffrey Pennington, Vinay Rao, Jascha Sohl-Dickstein, Samuel S. Schoenholz:
A Mean Field Theory of Batch Normalization. ICLR (Poster) 2019 - [c6]Hadi Salman, Greg Yang, Huan Zhang, Cho-Jui Hsieh, Pengchuan Zhang:
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks. NeurIPS 2019: 9832-9842 - [c5]Greg Yang:
Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes. NeurIPS 2019: 9947-9960 - [c4]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: 11289-11300 - [i14]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 abs/1901.08987 (2019) - [i13]Matthew J. Hausknecht, Ricky Loynd, Greg Yang, Adith Swaminathan, Jason D. Williams:
NAIL: A General Interactive Fiction Agent. CoRR abs/1902.04259 (2019) - [i12]Greg Yang:
Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel Derivation. CoRR abs/1902.04760 (2019) - [i11]Greg Yang, Jeffrey Pennington, Vinay Rao, Jascha Sohl-Dickstein, Samuel S. Schoenholz:
A Mean Field Theory of Batch Normalization. CoRR abs/1902.08129 (2019) - [i10]Hadi Salman, Greg Yang, Huan Zhang, Cho-Jui Hsieh, Pengchuan Zhang:
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks. CoRR abs/1902.08722 (2019) - [i9]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 abs/1906.04584 (2019) - [i8]Greg Yang, Hadi Salman:
A Fine-Grained Spectral Perspective on Neural Networks. CoRR abs/1907.10599 (2019) - [i7]Justin Chen, Christopher Eur, Greg Yang, Mengyuan Zhang
:
Free resolutions of function classes via order complexes. CoRR abs/1909.02159 (2019) - [i6]Greg Yang:
Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes. CoRR abs/1910.12478 (2019) - 2018
- [c3]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: 56:1-56:16 - 2017
- [c2]Greg Yang, Alexander M. Rush
Lie-Access Neural Turing Machines. ICLR (Poster) 2017 - [c1]Greg Yang, Samuel S. Schoenholz:
Mean Field Residual Networks: On the Edge of Chaos. NIPS 2017: 7103-7114 - [i5]Greg Yang:
A Homological Theory of Functions. CoRR abs/1701.02302 (2017) - [i4]Greg Yang, Samuel S. Schoenholz:
Mean Field Residual Networks: On the Edge of Chaos. CoRR abs/1712.08969 (2017) - 2016
- [i3]Greg Yang:
Lie Access Neural Turing Machine. CoRR abs/1602.08671 (2016) - [i2]Greg Yang, Alexander M. Rush:
Lie-Access Neural Turing Machines. CoRR abs/1611.02854 (2016) - 2015
- [j1]Greg Yang:
Computability of validity and satisfiability in probability logics over finite and countable models. J. Appl. Non Class. Logics 25(4): 324-372 (2015) - 2014
- [i1]Greg Yang:
Computabilities of Validity and Satisfiability in Probability Logics over Finite and Countable Models. CoRR abs/1410.3059 (2014)
Coauthor Index
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