Roger B. Grosse

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

Venues

Active years

2007–2023

Best venue rank

Where they publish

Papers

39 indexed papers, newest first.

Year	Venue	Title	Authors
2023	ACL	Discovering Language Model Behaviors with Model-Written Evaluations.	Ethan Perez, Sam Ringer, Kamile Lukosiute, Karina Nguyen, Edwin Chen, Scott Heiner, Craig Pettit, Catherine Olsson, Sandipan Kundu, Saurav Kadavath, Andy Jones, Anna Chen, Benjamin Mann, Brian Israel, Bryan Seethor, Cameron McKinnon, Christopher Olah, Da Yan, Daniela Amodei, Dario Amodei, Dawn Drain, Dustin Li, Eli Tran-Johnson, Guro Khundadze, Jackson Kernion, James Landis, Jamie Kerr, Jared Mueller, Jeeyoon Hyun, Joshua Landau, Kamal Ndousse, Landon Goldberg, Liane Lovitt, Martin Lucas, Michael Sellitto, Miranda Zhang, Neerav Kingsland, Nelson Elhage, Nicholas Joseph, Noem Mercado, Nova DasSarma, Oliver Rausch, Robin Larson, Sam McCandlish, Scott Johnston, Shauna Kravec, Sheer El Showk, Tamera Lanham, Timothy Telleen-Lawton, Tom Brown, Tom Henighan, Tristan Hume, Yuntao Bai, Zac Hatfield-Dodds, Jack Clark, Samuel R. Bowman, Amanda Askell, Roger B. Grosse, Danny Hernandez, Deep Ganguli, Evan Hubinger, Nicholas Schiefer, Jared Kaplan
2022	AISTATS	Near-optimal Local Convergence of Alternating Gradient Descent-Ascent for Minimax Optimization.	Guodong Zhang, Yuanhao Wang, Laurent Lessard, Roger B. Grosse
2022	ICML	On Implicit Bias in Overparameterized Bilevel Optimization.	Paul Vicol, Jonathan P. Lorraine, Fabian Pedregosa, David Duvenaud, Roger B. Grosse
2021	AAAI	Learning Branching Heuristics for Propositional Model Counting.	Pashootan Vaezipoor, Gil Lederman, Yuhuai Wu, Chris J. Maddison, Roger B. Grosse, Sanjit A. Seshia, Fahiem Bacchus
2021	AISTATS	Understanding and Mitigating Exploding Inverses in Invertible Neural Networks.	Jens Behrmann, Paul Vicol, Kuan-Chieh Wang, Roger B. Grosse, Jrn-Henrik Jacobsen
2021	AISTATS	Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?	Chaoqi Wang, Shengyang Sun, Roger B. Grosse
2021	ICML	On Monotonic Linear Interpolation of Neural Network Parameters.	James Lucas, Juhan Bae, Michael R. Zhang, Stanislav Fort, Richard S. Zemel, Roger B. Grosse
2021	ICML	Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition.	Shengyang Sun, Jiaxin Shi, Andrew Gordon Wilson, Roger B. Grosse
2021	ICML	LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning.	Yuhuai Wu, Markus N. Rabe, Wenda Li, Jimmy Ba, Roger B. Grosse, Christian Szegedy
2020	ICLR	Picking Winning Tickets Before Training by Preserving Gradient Flow.	Chaoqi Wang, Guodong Zhang, Roger B. Grosse
2020	ICML	Evaluating Lossy Compression Rates of Deep Generative Models.	Sicong Huang, Alireza Makhzani, Yanshuai Cao, Roger B. Grosse
2019	ICLR	TimbreTron: A WaveNet(CycleGAN(CQT(Audio))) Pipeline for Musical Timbre Transfer.	Sicong Huang, Qiyang Li, Cem Anil, Xuchan Bao, Sageev Oore, Roger B. Grosse
2019	ICLR	Aggregated Momentum: Stability Through Passive Damping.	James Lucas, Shengyang Sun, Richard S. Zemel, Roger B. Grosse
2019	ICLR	Understanding Posterior Collapse in Generative Latent Variable Models.	James Lucas, George Tucker, Roger B. Grosse, Mohammad Norouzi
2019	ICLR	Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions.	Matthew MacKay, Paul Vicol, Jonathan Lorraine, David Duvenaud, Roger B. Grosse
2019	ICLR	Functional variational Bayesian Neural Networks.	Shengyang Sun, Guodong Zhang, Jiaxin Shi, Roger B. Grosse
2019	ICLR	Three Mechanisms of Weight Decay Regularization.	Guodong Zhang, Chaoqi Wang, Bowen Xu, Roger B. Grosse
2019	ICML	Sorting Out Lipschitz Function Approximation.	Cem Anil, James Lucas, Roger B. Grosse
2019	ICML	EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis.	Chaoqi Wang, Roger B. Grosse, Sanja Fidler, Guodong Zhang
2018	ICLR	Isolating Sources of Disentanglement in Variational Autoencoders.	Tian Qi Chen, Xuechen Li, Roger B. Grosse, David Duvenaud
2018	ICLR	Stochastic Gradient Langevin dynamics that Exploit Neural Network Structure.	Zachary Nado, Jasper Snoek, Roger B. Grosse, David Duvenaud, Bowen Xu, James Martens
2018	ICLR	Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches.	Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, Roger B. Grosse
2018	ICLR	Understanding Short-Horizon Bias in Stochastic Meta-Optimization.	Yuhuai Wu, Mengye Ren, Renjie Liao, Roger B. Grosse
2018	ICML	Differentiable Compositional Kernel Learning for Gaussian Processes.	Shengyang Sun, Guodong Zhang, Chaoqi Wang, Wenyuan Zeng, Jiaman Li, Roger B. Grosse
2018	ICML	Adversarial Distillation of Bayesian Neural Network Posteriors.	Kuan-Chieh Wang, Paul Vicol, James Lucas, Li Gu, Roger B. Grosse, Richard S. Zemel
2018	ICML	Noisy Natural Gradient as Variational Inference.	Guodong Zhang, Shengyang Sun, David Duvenaud, Roger B. Grosse
2017	AISTATS	Discovering and Exploiting Additive Structure for Bayesian Optimization.	Jacob R. Gardner, Chuan Guo, Kilian Q. Weinberger, Roman Garnett, Roger B. Grosse
2017	ICLR	Distributed Second-Order Optimization using Kronecker-Factored Approximations.	Jimmy Ba, Roger B. Grosse, James Martens
2017	ICLR	On the Quantitative Analysis of Decoder-Based Generative Models.	Yuhuai Wu, Yuri Burda, Ruslan Salakhutdinov, Roger B. Grosse
2016	ICML	A Kronecker-factored approximate Fisher matrix for convolution layers.	Roger B. Grosse, James Martens
2015	AISTATS	Accurate and conservative estimates of MRF log-likelihood using reverse annealing.	Yuri Burda, Roger B. Grosse, Ruslan Salakhutdinov
2015	ICML	Scaling up Natural Gradient by Sparsely Factorizing the Inverse Fisher Matrix.	Roger B. Grosse, Ruslan Salakhutdinov
2015	ICML	Optimizing Neural Networks with Kronecker-factored Approximate Curvature.	James Martens, Roger B. Grosse
2014	AAAI	Automatic Construction and Natural-Language Description of Nonparametric Regression Models.	James Robert Lloyd, David Duvenaud, Roger B. Grosse, Joshua B. Tenenbaum, Zoubin Ghahramani
2013	ICML	Structure Discovery in Nonparametric Regression through Compositional Kernel Search.	David Duvenaud, James Robert Lloyd, Roger B. Grosse, Joshua B. Tenenbaum, Zoubin Ghahramani
2012	UAI	Exploiting compositionality to explore a large space of model structures.	Roger B. Grosse, Ruslan Salakhutdinov, William T. Freeman, Joshua B. Tenenbaum
2009	ICCV	Ground truth dataset and baseline evaluations for intrinsic image algorithms.	Roger B. Grosse, Micah K. Johnson, Edward H. Adelson, William T. Freeman
2009	ICML	Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations.	Honglak Lee, Roger B. Grosse, Rajesh Ranganath, Andrew Y. Ng
2007	UAI	Shift-Invariance Sparse Coding for Audio Classification.	Roger B. Grosse, Rajat Raina, Helen Kwong, Andrew Y. Ng