Tim Brys
Reinforcement Learning · 2015–2016
A researcher in the Science corpus: 3 papers; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Reinforcement Learning — 37 citations into it
- Artificial Intelligence — 25 citations into it
- Meta & Continual Learning — 5 citations into it
Whom Tim Brys trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard S. Sutton
- Matthew E. Taylor
- Andrew Barto
- Gavin Adrian Rummery
- Eric Wiewiora
- Peter Stone
- Andrew Y. Ng
- Martin L. Puterman
- Stephen W. Carden
- Mahesan Niranjan
Who trusts Tim Brys overall
- Zhuangdi Zhu
- Ahmed Hussein
- Todd Hester
- Michael Gimelfarb
- Dipendra Kumar Misra
- Halit Bener Suay
- Kaixiang Lin
- Allan Zhou
- Matej Vecerík
- Mohamed Medhat Gaber
Papers from Tim Brys's perspective
Ordered by how strongly the researchers Tim Brys trusts endorse each paper. Same corpus, a different order for every researcher.
- Reinforcement Learning: An Introduction
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping
Their papers
- Learning from Demonstration for Shaping through Inverse Reinforcement Learning (2016) — 81 citations
- Policy Transfer using Reward Shaping (2015) — 91 citations
- Reinforcement Learning from Demonstration through Shaping (2015) — 242 citations