Fred Cummins
Cognitive Neuroscience · 2000–2013
A researcher in the Science corpus: 2 papers; trusts 41 researchers and is trusted by 224 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 76 citations into it; #4,262 of 10,852 by trust here, #8,899 by citations
- Social Psychology — 65 citations into it; #5,840 of 15,694 by trust here, #12,211 by citations
- Developmental and Educational Psychology — 29 citations into it; #3,096 of 8,223 by trust here, #5,956 by citations
- Experimental and Cognitive Psychology — 22 citations into it
- Sociology and Political Science — 11 citations into it
- Human-Computer Interaction — 8 citations into it
- Psychiatry and Mental health — 8 citations into it
- Optimization & Training — 6 citations into it
Whom Fred Cummins trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Daniel D. Hutto
- Manos Tsakiris
- F. D. de Waal
- Patrick Haggard
- Karl J. Friston
- Jean Decety
- Paul Cisek
- Vittorio Gallese †
- Giacomo Rizzolatti
- Patricia K. Kuhl
Who trusts Fred Cummins overall
- J. Urgen Schmidhuber
- Erik Rietveld
- Zachary Chase Lipton
- Yoshua Bengio
- Julian Kiverstein
- Quoc V. Le
- Felix Alexander Gers
- Sjoerd van Steenkiste
- Rupesh Kumar Srivastava
- Sergey Levine
Papers from Fred Cummins's perspective
Ordered by how strongly the researchers Fred Cummins trusts endorse each paper. Same corpus, a different order for every researcher.
- Learning long-term dependencies with gradient descent is difficult
- Untersuchungen zu dynamischen neuronalen Netzen
- An integrative theory of prefrontal cortex function.
- A Focused Backpropagation Algorithm for Temporal Pattern Recognition
- The mirror-neuron system. (Annual Review of Neuroscience)
- An Efficient Gradient-Based Algorithm for On-Line Training of Recurrent Network Trajectories
- The Ecological Approach to Visual Perception
- Gradient-based learning algorithms for recurrent networks and their computational complexity
- ImageNet classification with deep convolutional neural networks
- Reinforcement Learning: An Introduction
Their papers
- Learning to Forget: Continual Prediction with LSTM (2000) — 7,541 citations
- Merging second-person and first-person neuroscience (2013) — 658 citations