Roger B Grosse
24 papers · 2013–2023 · 3 conferences · across top CS/AI conferences
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neural network
(4)
stochastic gradient
(3)
annealed importance sampling
(3)
neural network optimization
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bayesian inference
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hyperparameter optimization
(2)
bilevel optimization
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variational inference
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convergence analysis
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game theory
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variational autoencoder
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principal component analysis
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image classification
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similarity-based reasoning
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multi-agent reinforcement learning
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kl divergence
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Papers
Similarity-based cooperative equilibrium
NIPS 2023
On Implicit Bias in Overparameterized Bilevel Optimization
ICML 2022
Proximal Learning With Opponent-Learning Awareness
NIPS 2022
If Influence Functions are the Answer, Then What is the Question?
NIPS 2022
Amortized Proximal Optimization
NIPS 2022
Path Independent Equilibrium Models Can Better Exploit Test-Time Computation
NIPS 2022
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise
NIPS 2021
LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning
ICML 2021
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
ICML 2021
On Monotonic Linear Interpolation of Neural Network Parameters
ICML 2021
Learning Branching Heuristics for Propositional Model Counting
AAAI 2021
Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response Jacobians
NIPS 2020
Regularized linear autoencoders recover the principal components, eventually
NIPS 2020
Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model
NIPS 2019
Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse
NIPS 2019
Fast Convergence of Natural Gradient Descent for Over-Parameterized Neural Networks
NIPS 2019
Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks
NIPS 2019
Isolating Sources of Disentanglement in Variational Autoencoders
NIPS 2018
Reversible Recurrent Neural Networks
NIPS 2018
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation
NIPS 2017
The Reversible Residual Network: Backpropagation Without Storing Activations
NIPS 2017
Measuring the reliability of MCMC inference with bidirectional Monte Carlo
NIPS 2016
Learning Wake-Sleep Recurrent Attention Models
NIPS 2015
Annealing between distributions by averaging moments
NIPS 2013