Grosse, Roger B.

36 publications

NeurIPS 2023 Similarity-Based Cooperative Equilibrium Caspar Oesterheld, Johannes Treutlein, Roger B Grosse, Vincent Conitzer, Jakob Foerster

AISTATS 2022 Near-Optimal Local Convergence of Alternating Gradient Descent-Ascent for Minimax Optimization Guodong Zhang, Yuanhao Wang, Laurent Lessard, Roger B. Grosse

NeurIPS 2022 Amortized Proximal Optimization Juhan Bae, Paul Vicol, Jeff Z. HaoChen, Roger B Grosse

NeurIPS 2022 If Influence Functions Are the Answer, Then What Is the Question? Juhan Bae, Nathan Ng, Alston Lo, Marzyeh Ghassemi, Roger B Grosse

ICML 2022 On Implicit Bias in Overparameterized Bilevel Optimization Paul Vicol, Jonathan P Lorraine, Fabian Pedregosa, David Duvenaud, Roger B Grosse

NeurIPS 2022 Path Independent Equilibrium Models Can Better Exploit Test-Time Computation Cem Anil, Ashwini Pokle, Kaiqu Liang, Johannes Treutlein, Yuhuai Wu, Shaojie Bai, J. Zico Kolter, Roger B Grosse

NeurIPS 2022 Proximal Learning with Opponent-Learning Awareness Stephen Zhao, Chris Lu, Roger B Grosse, Jakob Foerster

NeurIPS 2021 Differentiable Annealed Importance Sampling and the Perils of Gradient Noise Guodong Zhang, Kyle Hsu, Jianing Li, Chelsea Finn, Roger B Grosse

ICML 2021 LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning Yuhuai Wu, Markus N Rabe, Wenda Li, Jimmy Ba, Roger B Grosse, Christian Szegedy

AAAI 2021 Learning Branching Heuristics for Propositional Model Counting Pashootan Vaezipoor, Gil Lederman, Yuhuai Wu, Chris J. Maddison, Roger B. Grosse, Sanjit A. Seshia, Fahiem Bacchus

ICML 2021 On Monotonic Linear Interpolation of Neural Network Parameters James R Lucas, Juhan Bae, Michael R Zhang, Stanislav Fort, Richard Zemel, Roger B Grosse

ICML 2021 Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition Shengyang Sun, Jiaxin Shi, Andrew Gordon Gordon Wilson, Roger B Grosse

NeurIPS 2020 Delta-STN: Efficient Bilevel Optimization for Neural Networks Using Structured Response Jacobians Juhan Bae, Roger B Grosse

NeurIPS 2020 Regularized Linear Autoencoders Recover the Principal Components, Eventually Xuchan Bao, James Lucas, Sushant Sachdeva, Roger B Grosse

NeurIPS 2019 Don't Blame the ELBO! a Linear VAE Perspective on Posterior Collapse James Lucas, George Tucker, Roger B Grosse, Mohammad Norouzi

NeurIPS 2019 Fast Convergence of Natural Gradient Descent for Over-Parameterized Neural Networks Guodong Zhang, James Martens, Roger B Grosse

NeurIPS 2019 Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks Qiyang Li, Saminul Haque, Cem Anil, James Lucas, Roger B Grosse, Joern-Henrik Jacobsen

ICLR 2019 TimbreTron: A WaveNet(CycleGAN(CQT(Audio))) Pipeline for Musical Timbre Transfer Sicong Huang, Qiyang Li, Cem Anil, Xuchan Bao, Sageev Oore, Roger B. Grosse

NeurIPS 2019 Which Algorithmic Choices Matter at Which Batch Sizes? Insights from a Noisy Quadratic Model Guodong Zhang, Lala Li, Zachary Nado, James Martens, Sushant Sachdeva, George Dahl, Chris Shallue, Roger B Grosse

NeurIPS 2018 Isolating Sources of Disentanglement in Variational Autoencoders Ricky T. Q. Chen, Xuechen Li, Roger B Grosse, David K. Duvenaud

NeurIPS 2018 Reversible Recurrent Neural Networks Matthew MacKay, Paul Vicol, Jimmy Ba, Roger B Grosse

AISTATS 2017 Discovering and Exploiting Additive Structure for Bayesian Optimization Jacob R. Gardner, Chuan Guo, Kilian Q. Weinberger, Roman Garnett, Roger B. Grosse

ICLR 2017 Distributed Second-Order Optimization Using Kronecker-Factored Approximations Jimmy Ba, Roger B. Grosse, James Martens

ICLR 2017 On the Quantitative Analysis of Decoder-Based Generative Models Yuhuai Wu, Yuri Burda, Ruslan Salakhutdinov, Roger B. Grosse

NeurIPS 2017 Scalable Trust-Region Method for Deep Reinforcement Learning Using Kronecker-Factored Approximation Yuhuai Wu, Elman Mansimov, Roger B Grosse, Shun Liao, Jimmy Ba

NeurIPS 2017 The Reversible Residual Network: Backpropagation Without Storing Activations Aidan N Gomez, Mengye Ren, Raquel Urtasun, Roger B Grosse

ICLR 2016 Importance Weighted Autoencoders Yuri Burda, Roger B. Grosse, Ruslan Salakhutdinov

NeurIPS 2016 Measuring the Reliability of MCMC Inference with Bidirectional Monte Carlo Roger B Grosse, Siddharth Ancha, Daniel M. Roy

AISTATS 2015 Accurate and Conservative Estimates of MRF Log-Likelihood Using Reverse Annealing Yuri Burda, Roger B. Grosse, Ruslan Salakhutdinov

NeurIPS 2015 Learning Wake-Sleep Recurrent Attention Models Jimmy Ba, Ruslan Salakhutdinov, Roger B Grosse, Brendan J. Frey

AAAI 2014 Automatic Construction and Natural-Language Description of Nonparametric Regression Models James Robert Lloyd, David Duvenaud, Roger B. Grosse, Joshua B. Tenenbaum, Zoubin Ghahramani

NeurIPS 2013 Annealing Between Distributions by Averaging Moments Roger B Grosse, Chris J Maddison, Ruslan Salakhutdinov

UAI 2012 Exploiting Compositionality to Explore a Large Space of Model Structures Roger B. Grosse, Ruslan Salakhutdinov, William T. Freeman, Joshua B. Tenenbaum

ICML 2009 Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations Honglak Lee, Roger B. Grosse, Rajesh Ranganath, Andrew Y. Ng

ICCV 2009 Ground Truth Dataset and Baseline Evaluations for Intrinsic Image Algorithms Roger B. Grosse, Micah K. Johnson, Edward H. Adelson, William T. Freeman

UAI 2007 Shift-Invariance Sparse Coding for Audio Classification Roger B. Grosse, Rajat Raina, Helen Kwong, Andrew Y. Ng