Taylor W. Killian
Reinforcement Learning · 2016–2018
A researcher in the Science corpus: 3 papers; trusts 42 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Reinforcement Learning — 33 citations into it
- Artificial Intelligence — 31 citations into it; #13,716 of 35,345 by trust here, #23,731 by citations
- Probabilistic & Bayesian Methods — 13 citations into it
- Representation & Self-Supervised Learning — 6 citations into it
- Cognitive Neuroscience — 5 citations into it
- Electrical and Electronic Engineering — 5 citations into it
- Management Science and Operations Research — 5 citations into it
- Medical & Health AI — 5 citations into it
Whom Taylor W. Killian trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Marc Peter Deisenroth
- Neil D. Lawrence
- Damien Ernst
- Carl E. Rasmussen
- Richard S. Sutton
- Diederik P. Kingma
- Finale Doshi-Velez
- Tom Schaul
- Geoffrey E. Hinton
- Volodymyr Mnih
Who trusts Taylor W. Killian overall
- Chao Yu
- Jiayu Yao
- Soumya Ghosh
- Roberta Raileanu
- Jiming Liu
- Steindór Sæmundsson
- Finale Doshi-Velez
- Shamim Nemati
- Maxwell Goldstein
- Katja Hofmann
Papers from Taylor W. Killian's perspective
Ordered by how strongly the researchers Taylor W. Killian trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- Reinforcement Learning: An Introduction
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)