Gabriel Kalweit

Reinforcement Learning · 2017

A researcher in the Science corpus: 1 paper; trusts 30 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 21 citations into it; #986 of 2,242 by trust here, #1,822 by citations
• Artificial Intelligence — 19 citations into it
• Control and Systems Engineering — 6 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it; #779 of 1,525 by trust here, #1,075 by citations

Whom Gabriel Kalweit trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. David Silver
2. Rémi Coulom
3. E. Todorov
4. Richard S. Sutton
5. Levente Kocsis
6. Weiwei Li
7. Volodymyr Mnih
8. Geoffrey E. Hinton
9. Ian Osband
10. David John Cameron MacKay

Who trusts Gabriel Kalweit overall

1. Danijar Hafner
2. Michael Janner
3. Ignasi Clavera
4. Sergey Levine
5. Jacob Buckman
6. Shagun Sodhani
7. Vladimir Feinberg
8. Lukasz Kaiser
9. Igor Mordatch
10. Timothy P. Lillicrap

Papers from Gabriel Kalweit's perspective

Ordered by how strongly the researchers Gabriel Kalweit trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. Reinforcement Learning: An Introduction

Their papers

• Uncertainty-driven Imagination for Continuous Deep Reinforcement Learning (2017) — 134 citations