G. Dudek
Artificial Intelligence · 1997–2019
A researcher in the Science corpus: 7 papers; trusts 87 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 58 citations into it; #26,448 of 35,345 by trust here, #20,836 by citations
- Reinforcement Learning — 50 citations into it; #1,781 of 2,242 by trust here, #1,778 by citations
- Computer Vision and Pattern Recognition — 18 citations into it; #18,202 of 21,575 by trust here, #14,478 by citations
- Control and Systems Engineering — 15 citations into it
- Management Science and Operations Research — 15 citations into it
- Computational Theory and Mathematics — 12 citations into it
- Probabilistic & Bayesian Methods — 10 citations into it
- Robotics & Control — 9 citations into it
Whom G. Dudek trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Alex Krizhevsky
- Ilya Sutskever
- Yann LeCun
- Richard S. Sutton
- Radford M. Neal
- Jimmy Ba
- Alex Graves
Who trusts G. Dudek overall
Papers from G. Dudek's perspective
Ordered by how strongly the researchers G. Dudek 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Synthesizing Neural Network Controllers with Probabilistic Model-Based Reinforcement Learning (2018) — 41 citations
- Benchmark Environments for Multitask Learning in Continuous Domains (2017) — 42 citations
- Generating Adversarial Driving Scenarios in High-Fidelity Simulators (2019) — 149 citations
- Learning legged swimming gaits from experience (2015) — 41 citations
- Negotiation-based collaborative planning between supply chains partners (2005) — 309 citations
- Computational principles of mobile robotics (2000) — 858 citations
- A Mobile Robot That Learns Its Place (1997)