Szymon Sidor
Artificial Intelligence · 2017–2023
A researcher in the Science corpus: 9 papers; trusts 66 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 181 citations into it; #16,256 of 35,345 by trust here, #1,914 by citations
- Reinforcement Learning — 139 citations into it; #1,387 of 2,242 by trust here, #194 by citations
- Computer Vision and Pattern Recognition — 47 citations into it
- Optimization & Training — 43 citations into it
- Control and Systems Engineering — 39 citations into it
- Management Science and Operations Research — 33 citations into it
- Computational Theory and Mathematics — 18 citations into it
- Robotics & Control — 15 citations into it
Whom Szymon Sidor trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Ronald J. Williams
- Geoffrey E. Hinton
- Jimmy Ba
- John Schulman
- Richard S. Sutton
- Volodymyr Mnih
- Yoshua Bengio
- Ian Osband
- Alex Krizhevsky
Who trusts Szymon Sidor overall
- Tim Salimans
- Raghuram Mandyam Annasamy
- Shangtong Zhang
- Borislav Mavrin
- Seyed Kamyar Seyed Ghasemipour
- Yuri Burda
- Gaon An
Papers from Szymon Sidor's perspective
Ordered by how strongly the researchers Szymon Sidor trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- GENERATIVE ADVERSARIAL NETS
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Learning dexterous in-hand manipulation (2018) — 2,231 citations
- Parameter Space Noise for Exploration (2017) — 689 citations
- Dota 2 with Large Scale Deep Reinforcement Learning (2019) — 2,179 citations
- Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics (2017) — 246 citations
- Emergent Complexity via Multi-Agent Competition (2017) — 435 citations
- GPT-4 Technical Report (2023) — 26,133 citations
- Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer (2022) — 295 citations
- Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer (2021) — 177 citations
- UCB EXPLORATION VIA Q-ENSEMBLES (2018) — 151 citations