Carlton Downey

Artificial Intelligence · 2010–2018

A researcher in the Science corpus: 4 papers; trusts 43 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 35 citations into it; #22,954 of 35,345 by trust here, #20,836 by citations
• Model Architectures — 13 citations into it; #1,656 of 2,278 by trust here, #2,128 by citations
• Representation & Self-Supervised Learning — 13 citations into it
• Reinforcement Learning — 11 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it
• Probabilistic & Bayesian Methods — 10 citations into it
• Natural Language Processing — 7 citations into it
• Statistical Learning Theory — 6 citations into it

Whom Carlton Downey trusts overall

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

1. Andrew Barto
2. Yoshua Bengio
3. Byron Boots
4. Sepp Hochreiter
5. Richard S. Sutton
6. Geoffrey E. Hinton
7. J. Urgen Schmidhuber
8. Kyunghyun Cho
9. Alex Smola
10. Sebastian Thrun

Who trusts Carlton Downey overall

1. Philip S. Thomas
2. George Dimitri Konidaris
3. Krzysztof Marcin Choromanski
4. Martha White
5. Bryan Lim
6. Stefan Elfwing
7. Michael Gimelfarb
8. Shota Horiguchi
9. Scott Niekum
10. Yusuke Fujita

Papers from Carlton Downey's perspective

Ordered by how strongly the researchers Carlton Downey 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. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Predictive State Recurrent Neural Networks (2017) — 58 citations
• Speaker Diarization with LSTM (2017) — 344 citations
• Initialization matters: Orthogonal Predictive State Recurrent Neural Networks (2018) — 22 citations
• Temporal Difference Bayesian Model Averaging: A Bayesian Perspective on Adapting Lambda (2010) — 28 citations