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If Influence Functions are the Answer, Then What is the Question?


Sep 12, 2022
Juhan Bae, Nathan Ng, Alston Lo, Marzyeh Ghassemi, Roger Grosse

* 28 pages, 6 figures 

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Amortized Proximal Optimization


Feb 28, 2022
Juhan Bae, Paul Vicol, Jeff Z. HaoChen, Roger Grosse

* 37 pages, 30 figures 

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Learning to Give Checkable Answers with Prover-Verifier Games


Aug 27, 2021
Cem Anil, Guodong Zhang, Yuhuai Wu, Roger Grosse


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Differentiable Annealed Importance Sampling and the Perils of Gradient Noise


Jul 21, 2021
Guodong Zhang, Kyle Hsu, Jianing Li, Chelsea Finn, Roger Grosse

* 22 pages 

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Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition


Jun 10, 2021
Shengyang Sun, Jiaxin Shi, Andrew Gordon Wilson, Roger Grosse

* ICML2021, 21 pages 

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Analyzing Monotonic Linear Interpolation in Neural Network Loss Landscapes


Apr 23, 2021
James Lucas, Juhan Bae, Michael R. Zhang, Stanislav Fort, Richard Zemel, Roger Grosse

* 15 pages in main paper, 4 pages of references, 24 pages in appendix. 29 figures in total 

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Don't Fix What ain't Broke: Near-optimal Local Convergence of Alternating Gradient Descent-Ascent for Minimax Optimization


Feb 18, 2021
Guodong Zhang, Yuanhao Wang, Laurent Lessard, Roger Grosse


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LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning


Jan 15, 2021
Yuhuai Wu, Markus Rabe, Wenda Li, Jimmy Ba, Roger Grosse, Christian Szegedy

* 16 pages 

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Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?


Nov 06, 2020
Chaoqi Wang, Shengyang Sun, Roger Grosse


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Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response Jacobians


Oct 26, 2020
Juhan Bae, Roger Grosse

* Published as a conference paper at Neurips 2020 

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