Roger B. Grosse

According to our database1, Roger B. Grosse authored at least 40 papers between 2007 and 2018.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

Homepage:

On csauthors.net:

Bibliography

2018
Three Mechanisms of Weight Decay Regularization.
CoRR, 2018

Differentiable Compositional Kernel Learning for Gaussian Processes.
CoRR, 2018

Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches.
CoRR, 2018

Understanding Short-Horizon Bias in Stochastic Meta-Optimization.
CoRR, 2018

Isolating Sources of Disentanglement in Variational Autoencoders.
CoRR, 2018

Noisy Natural Gradient as Variational Inference.
Proceedings of the 35th International Conference on Machine Learning, 2018

Differentiable Compositional Kernel Learning for Gaussian Processes.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Noisy Natural Gradient as Variational Inference.
CoRR, 2017

Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation.
CoRR, 2017

The Reversible Residual Network: Backpropagation Without Storing Activations.
CoRR, 2017

Second-order Optimization for Deep Reinforcement Learning using Kronecker-factored Approximation.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

The Reversible Residual Network: Backpropagation Without Storing Activations.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
On the Quantitative Analysis of Decoder-Based Generative Models.
CoRR, 2016

A Kronecker-factored approximate Fisher matrix for convolution layers.
CoRR, 2016

Measuring the reliability of MCMC inference with bidirectional Monte Carlo.
CoRR, 2016

Measuring the reliability of MCMC inference with bidirectional Monte Carlo.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

A Kronecker-factored approximate Fisher matrix for convolution layers.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Optimizing Neural Networks with Kronecker-factored Approximate Curvature.
CoRR, 2015

Sandwiching the marginal likelihood using bidirectional Monte Carlo.
CoRR, 2015

Importance Weighted Autoencoders.
CoRR, 2015

Learning Wake-Sleep Recurrent Attention Models.
CoRR, 2015

Learning Wake-Sleep Recurrent Attention Models.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Optimizing Neural Networks with Kronecker-factored Approximate Curvature.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Scaling up Natural Gradient by Sparsely Factorizing the Inverse Fisher Matrix.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Accurate and conservative estimates of MRF log-likelihood using reverse annealing.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Model selection in compositional spaces.
PhD thesis, 2014

Automatic Construction and Natural-Language Description of Nonparametric Regression Models.
CoRR, 2014

Testing MCMC code.
CoRR, 2014

Accurate and Conservative Estimates of MRF Log-likelihood using Reverse Annealing.
CoRR, 2014

Automatic Construction and Natural-Language Description of Nonparametric Regression Models.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Structure Discovery in Nonparametric Regression through Compositional Kernel Search
CoRR, 2013

Annealing between distributions by averaging moments.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Structure Discovery in Nonparametric Regression through Compositional Kernel Search.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Exploiting compositionality to explore a large space of model structures
CoRR, 2012

Shift-Invariance Sparse Coding for Audio Classification
CoRR, 2012

Exploiting compositionality to explore a large space of model structures.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

2011
Unsupervised learning of hierarchical representations with convolutional deep belief networks.
Commun. ACM, 2011

2009
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Ground truth dataset and baseline evaluations for intrinsic image algorithms.
Proceedings of the IEEE 12th International Conference on Computer Vision, ICCV 2009, Kyoto, Japan, September 27, 2009

2007
Shift-Invariance Sparse Coding for Audio Classification.
Proceedings of the UAI 2007, 2007


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