Conor Heins

Cognitive Neuroscience · 2022

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 30 citations into it
• Artificial Intelligence — 18 citations into it
• Statistical and Nonlinear Physics — 16 citations into it
• Reinforcement Learning — 10 citations into it
• Probabilistic & Bayesian Methods — 9 citations into it
• Cognitive Science & Psychology — 5 citations into it
• Computational Theory and Mathematics — 5 citations into it

Whom Conor Heins trusts overall

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

1. David John Cameron MacKay
2. Karl J. Friston
3. Hilbert J. Kappen
4. Brian D. Ziebart
5. Matthew J. Beal
6. Sergey Levine
7. E. Todorov

Papers from Conor Heins's perspective

Ordered by how strongly the researchers Conor Heins 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. Information Theory, Inference, and Learning Algorithms
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Reinforcement Learning: An Introduction
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. What is Intrinsic Motivation? A Typology of Computational Approaches
9. Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• The free energy principle made simpler but not too simple (2022) — 151 citations