Lech Szymanski
Artificial Intelligence · 2018
A researcher in the Science corpus: 2 papers; trusts 27 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 34 citations into it; #20,788 of 35,345 by trust here, #17,776 by citations
- Computer Vision and Pattern Recognition — 17 citations into it; #18,795 of 21,575 by trust here, #14,478 by citations
- Reinforcement Learning — 16 citations into it
- Cognitive Neuroscience — 12 citations into it
- Meta & Continual Learning — 10 citations into it; #942 of 1,041 by trust here, #782 by citations
- Statistical and Nonlinear Physics — 5 citations into it
Whom Lech Szymanski trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Anthony V. Robins
- Geoffrey E. Hinton
- Richard S. Sutton
- Alex Krizhevsky
- Kaiming He
- Yoshua Bengio
- Hugo Caselles-Dupré
- Ilya Sutskever
- Bernard Ans
- Diederik P. Kingma
Who trusts Lech Szymanski overall
Papers from Lech Szymanski's perspective
Ordered by how strongly the researchers Lech Szymanski 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)
- Distilling the Knowledge in a Neural Network (arXiv.org)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Pseudo-Recursal: Solving the Catastrophic Forgetting Problem in Deep Neural Networks (2018) — 78 citations
- Pseudo-Rehearsal: Achieving Deep Reinforcement Learning without Catastrophic Forgetting (2018) — 121 citations