Ashesh Jain
Computer Vision and Pattern Recognition · 2006–2020
A researcher in the Science corpus: 6 papers; trusts 583 researchers and is trusted by 72 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 150 citations into it; #5,183 of 21,575 by trust here, #4,750 by citations
- Artificial Intelligence — 79 citations into it; #3,925 of 35,345 by trust here, #3,687 by citations
- Control and Systems Engineering — 57 citations into it
- Reinforcement Learning — 46 citations into it; #577 of 2,242 by trust here, #565 by citations
- Aerospace Engineering — 42 citations into it; #1,662 of 6,421 by trust here, #1,890 by citations
- Robotics & Control — 37 citations into it
- Automotive Engineering — 19 citations into it
- Model Architectures — 19 citations into it; #857 of 2,278 by trust here, #906 by citations
Whom Ashesh Jain trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Thorsten Joachims
- Yann LeCun
- Nathan D. Ratliff
- Yoshua Bengio
- Alex Graves
- Ilya Sutskever
- Alex Krizhevsky
- Kaiming He
- Pieter Abbeel
Who trusts Ashesh Jain overall
- Sergey Levine
- Pieter Abbeel
- Anca Dragan
- Nathan D. Ratliff
- J. Bagnell
- Chelsea Finn
- Andrea V. Bajcsy
- Jun Liu
- Kun Li
- Vladlen Koltun
Papers from Ashesh Jain's perspective
Ordered by how strongly the researchers Ashesh Jain 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)
- 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
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Structural-RNN: Deep Learning on Spatio-Temporal Graphs (2015) — 1,178 citations
- Maximum margin planning (2006) — 815 citations
- Learning Trajectory Preferences for Manipulators via Iterative Improvement (2013) — 141 citations
- One Thousand and One Hours: Self-driving Motion Prediction Dataset (2020) — 483 citations
- Learning preferences for manipulation tasks from online coactive feedback (2015) — 132 citations
- PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation (2017) — 739 citations