Iain Dunning

Artificial Intelligence · 2013–2019

A researcher in the Science corpus: 10 papers; trusts 45 researchers and is trusted by 47 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 176 citations into it; #7,726 of 35,345 by trust here, #2,158 by citations
• Reinforcement Learning — 131 citations into it; #890 of 2,242 by trust here, #225 by citations
• Management Science and Operations Research — 47 citations into it; #6,045 of 11,946 by trust here, #205 by citations
• Computational Theory and Mathematics — 26 citations into it; #7,715 of 12,182 by trust here, #234 by citations
• Optimization & Training — 23 citations into it
• Computer Networks and Communications — 17 citations into it; #1,972 of 9,886 by trust here, #3,862 by citations
• Hardware and Architecture — 10 citations into it; #209 of 1,551 by trust here, #595 by citations
• ML Systems & Hardware — 8 citations into it

Whom Iain Dunning trusts overall

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

1. Johan Efberg
2. Joel A. E. Andersson
3. Uwe Naumann
4. Message Passing Interface Forum
5. Diomidis D. Spinellis
6. Jeff Bezanson
7. Andreas Griewank
8. David L. Applegate
9. Richard S. Sutton
10. Michael Grant

Who trusts Iain Dunning overall

1. Velibor V. Misic
2. Dragos Florin Ciocan
3. Miles Lubin
4. Brendan O'Donoghue
5. Xuezhou Zhang
6. Dimitris J. Bertsimas
7. Jackson Gorham
8. Adam N. Elmachtoub
9. Vincent Tjeng
10. Laurent Lessard

Papers from Iain Dunning's perspective

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

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

Their papers

• IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures (2018) — 1,890 citations
• Population Based Training of Neural Networks (2017) — 896 citations
• Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning (2018) — 170 citations
• The Hanabi Challenge: A New Frontier for AI Research (2019) — 429 citations
• Malthusian Reinforcement Learning (2018) — 43 citations
• Inequity aversion improves cooperation in intertemporal social dilemmas (2018) — 271 citations
• Learning Fast Optimizers for Contextual Stochastic Integer Programs (2018) — 23 citations
• Human-level performance in 3D multiplayer games with population-based reinforcement learning (2018) — 819 citations
• JuMP: A Modeling Language for Mathematical Optimization (2015) — 1,563 citations
• Computing in Operations Research Using Julia (2013) — 361 citations