Rui Ponte Costa
Cognitive Neuroscience · 2018–2019
A researcher in the Science corpus: 2 papers; trusts 11 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 59 citations into it; #4,821 of 10,852 by trust here, #5,528 by citations
- Artificial Intelligence — 29 citations into it
- Electrical and Electronic Engineering — 25 citations into it; #6,486 of 16,539 by trust here, #8,802 by citations
- Cellular and Molecular Neuroscience — 18 citations into it; #1,331 of 2,998 by trust here, #2,534 by citations
- Computer Vision and Pattern Recognition — 18 citations into it
- Optimization & Training — 7 citations into it
Whom Rui Ponte Costa trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Geoffrey E. Hinton
- Randall C. O’Reilly
- David E. Rumelhart
- Timothy P. Lillicrap
- Xiaohui Xie
- Benjamin Scellier
- Richard S. Sutton
- Ronald J. Williams
- David H. Ackley
Who trusts Rui Ponte Costa overall
Papers from Rui Ponte Costa's perspective
Ordered by how strongly the researchers Rui Ponte Costa 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)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Dendritic cortical microcircuits approximate the backpropagation algorithm (2018) — 373 citations
- A deep learning framework for neuroscience (2019) — 1,016 citations