Adam Villaflor
Artificial Intelligence · 2017–2018
A researcher in the Science corpus: 3 papers; trusts 45 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 48 citations into it; #15,584 of 35,345 by trust here, #12,083 by citations
- Reinforcement Learning — 45 citations into it; #1,200 of 2,242 by trust here, #1,118 by citations
- Computer Vision and Pattern Recognition — 34 citations into it; #15,800 of 21,575 by trust here, #13,269 by citations
- Control and Systems Engineering — 20 citations into it
- Aerospace Engineering — 18 citations into it; #4,282 of 6,421 by trust here, #3,072 by citations
- Robotics & Control — 18 citations into it; #265 of 609 by trust here, #395 by citations
- Optimization & Training — 6 citations into it
- Statistics and Probability — 5 citations into it
Whom Adam Villaflor trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard S. Sutton
- Geoffrey E. Hinton
- Diederik P. Kingma
- Bradley Efron
- Alex Krizhevsky
- Yann LeCun
- Yoshua Bengio
- Sergey Levine
- Jan Peters
- Pieter Abbeel
Who trusts Adam Villaflor overall
- Gregory Kahn
- Sergey Levine
- Pieter Abbeel
- Kai Zhu
- Aviral Kumar
- Yarin Gal
- Benjamin Eysenbach
- Markus Wulfmeier
- Tingxiang Fan
- Tianhe Yu
Papers from Adam Villaflor's perspective
Ordered by how strongly the researchers Adam Villaflor 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
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- 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
- Self-Supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot Navigation (2017) — 315 citations
- Uncertainty-Aware Reinforcement Learning for Collision Avoidance (2017) — 337 citations
- Composable Action-Conditioned Predictors: Flexible Off-Policy Learning for Robot Navigation (2018) — 22 citations