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Computability of validity and satisfiability in probability logics over...
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)
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Lie-Access Neural Turing Machines.
Greg Yang, Alexander M. Rush: Lie-Access Neural Turing Machines. CoRR abs/1611.02854 (2016)
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Lie Access Neural Turing Machine.
Greg Yang: Lie Access Neural Turing Machine. CoRR abs/1602.08671 (2016)
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Mean Field Residual Networks: On the Edge of Chaos.
Greg Yang, Samuel S. Schoenholz: Mean Field Residual Networks: On the Edge of Chaos. CoRR abs/1712.08969 (2017)
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A Homological Theory of Functions.
Greg Yang: A Homological Theory of Functions. CoRR abs/1701.02302 (2017)
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Mean Field Residual Networks: On the Edge of Chaos.
Greg Yang, Samuel S. Schoenholz: Mean Field Residual Networks: On the Edge of Chaos. NIPS 2017: 7103-7114
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Lie-Access Neural Turing Machines.
Greg Yang, Alexander M. Rush: Lie-Access Neural Turing Machines. ICLR (Poster) 2017
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A Homological Theory of Functions: Nonuniform Boolean Complexity Separation...
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
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Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any...
Greg Yang: Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes. CoRR abs/1910.12478 (2019)
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Free resolutions of function classes via order complexes.
Justin Chen, Christopher Eur, Greg Yang, Mengyuan Zhang: Free resolutions of function classes via order complexes. CoRR abs/1909.02159 (2019)
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A Fine-Grained Spectral Perspective on Neural Networks.
Greg Yang, Hadi Salman: A Fine-Grained Spectral Perspective on Neural Networks. CoRR abs/1907.10599 (2019)
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Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers.
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...
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A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks.
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)
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A Mean Field Theory of Batch Normalization.
Greg Yang, Jeffrey Pennington, Vinay Rao, Jascha Sohl-Dickstein, Samuel S. Schoenholz: A Mean Field Theory of Batch Normalization. CoRR abs/1902.08129 (2019)
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Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process...
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)
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NAIL: A General Interactive Fiction Agent.
Matthew J. Hausknecht, Ricky Loynd, Greg Yang, Adith Swaminathan, Jason D. Williams: NAIL: A General Interactive Fiction Agent. CoRR abs/1902.04259 (2019)
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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: Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs. CoRR abs/1901.08987 (2019)
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Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers.
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:...
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Wide Feedforward or Recurrent Neural Networks of Any Architecture are...
Greg Yang: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes. NeurIPS 2019: 9947-9960
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A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks.
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
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A Mean Field Theory of Batch Normalization.
Greg Yang, Jeffrey Pennington, Vinay Rao, Jascha Sohl-Dickstein, Samuel S. Schoenholz: A Mean Field Theory of Batch Normalization. ICLR (Poster) 2019
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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: Bayesian Deep Convolutional Networks with Many Channels are...
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Feature Learning in Infinite-Width Neural Networks.
Greg Yang, J. Edward Hu: Feature Learning in Infinite-Width Neural Networks. CoRR abs/2011.14522 (2020)
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Tensor Programs III: Neural Matrix Laws.
Greg Yang: Tensor Programs III: Neural Matrix Laws. CoRR abs/2009.10685 (2020)
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Tensor Programs II: Neural Tangent Kernel for Any Architecture.
Greg Yang: Tensor Programs II: Neural Tangent Kernel for Any Architecture. CoRR abs/2006.14548 (2020)
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Improved Image Wasserstein Attacks and Defenses.
J. Edward Hu, Adith Swaminathan, Hadi Salman, Greg Yang: Improved Image Wasserstein Attacks and Defenses. CoRR abs/2004.12478 (2020)
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Black-box Smoothing: A Provable Defense for Pretrained Classifiers.
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)
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Randomized Smoothing of All Shapes and Sizes.
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)
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Denoised Smoothing: A Provable Defense for Pretrained Classifiers.
Hadi Salman, Mingjie Sun, Greg Yang, Ashish Kapoor, J. Zico Kolter: Denoised Smoothing: A Provable Defense for Pretrained Classifiers. NeurIPS 2020
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On Infinite-Width Hypernetworks.
Etai Littwin, Tomer Galanti, Lior Wolf, Greg Yang: On Infinite-Width Hypernetworks. NeurIPS 2020
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Randomized Smoothing of All Shapes and Sizes.
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
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Free resolutions of function classes via order complexes.
Justin Chen, Christopher Eur, Greg Yang, Mengyuan Zhang: Free resolutions of function classes via order complexes. Adv. Appl. Math. 120: 102074 (2020)
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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: CLUES: Few-Shot Learning Evaluation in Natural Language...
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Implicit Acceleration and Feature Learning in Infinitely Wide Neural Networks...
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...
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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: 3DB: A...
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Tensor Programs IIb: Architectural Universality of Neural Tangent Kernel...
Greg Yang, Etai Littwin: Tensor Programs IIb: Architectural Universality of Neural Tangent Kernel Training Dynamics. CoRR abs/2105.03703 (2021)
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Tensor Programs IIb: Architectural Universality Of Neural Tangent Kernel...
Greg Yang, Etai Littwin: Tensor Programs IIb: Architectural Universality Of Neural Tangent Kernel Training Dynamics. ICML 2021: 11762-11772
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Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks.
Greg Yang, Edward J. Hu: Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks. ICML 2021: 11727-11737
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High-dimensional Asymptotics of Feature Learning: How One Gradient Step...
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)
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Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter...
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...
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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: 3DB: A...
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Non-Gaussian Tensor Programs.
Eugene Golikov, Greg Yang: Non-Gaussian Tensor Programs. NeurIPS 2022
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High-dimensional Asymptotics of Feature Learning: How One Gradient Step...
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
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Efficient Computation of Deep Nonlinear Infinite-Width Neural Networks that...
Greg Yang, Michael Santacroce, Edward J. Hu: Efficient Computation of Deep Nonlinear Infinite-Width Neural Networks that Learn Features. ICLR 2022
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A Spectral Condition for Feature Learning.
Greg Yang, James B. Simon, Jeremy Bernstein: A Spectral Condition for Feature Learning. CoRR abs/2310.17813 (2023)
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Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks.
Greg Yang, Dingli Yu, Chen Zhu, Soufiane Hayou: Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks. CoRR abs/2310.02244 (2023)
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Tensor Programs IVb: Adaptive Optimization in the Infinite-Width Limit.
Greg Yang, Etai Littwin: Tensor Programs IVb: Adaptive Optimization in the Infinite-Width Limit. CoRR abs/2308.01814 (2023)
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Width and Depth Limits Commute in Residual Networks.
Soufiane Hayou, Greg Yang: Width and Depth Limits Commute in Residual Networks. CoRR abs/2302.00453 (2023)
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Width and Depth Limits Commute in Residual Networks.
Soufiane Hayou, Greg Yang: Width and Depth Limits Commute in Residual Networks. ICML 2023: 12700-12723
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Adaptive Optimization in the ∞-Width Limit.
Etai Littwin, Greg Yang: Adaptive Optimization in the ∞-Width Limit. ICLR 2023
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