Sachin Chitta
Artificial Intelligence · 2010–2015
A researcher in the Science corpus: 11 papers; trusts 32 researchers and is trusted by 27 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 39 citations into it; #14,459 of 35,345 by trust here, #10,942 by citations
- Reinforcement Learning — 37 citations into it; #1,476 of 2,242 by trust here, #1,519 by citations
- Control and Systems Engineering — 36 citations into it; #1,266 of 8,257 by trust here, #464 by citations
- Computer Vision and Pattern Recognition — 33 citations into it; #10,657 of 21,575 by trust here, #10,154 by citations
- Robotics & Control — 30 citations into it; #539 of 609 by trust here, #374 by citations
- Aerospace Engineering — 20 citations into it
- Biomedical Engineering — 12 citations into it; #9,041 of 10,734 by trust here, #6,932 by citations
- Mechanical Engineering — 6 citations into it
Whom Sachin Chitta trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Stefan Schaal
- Nathan D. Ratliff
- Morgan Quigley
- Auke Jan Ijspeert
- J. Bagnell
- Maxim Likhachev
- Steven M. LaValle
- Evangelos A. Theodorou
- Peter Pastor
- George Dimitri Konidaris
Who trusts Sachin Chitta overall
- John Schulman
- Felix Burget
- Ioan Alexandru Sucan
- Adithyavairavan Murali
- Anca Dragan
- Mrinal Kalakrishnan
- Berk Çalli
- Sergey Levine
- Yilin Wu
- Pieter Abbeel
Papers from Sachin Chitta's perspective
Ordered by how strongly the researchers Sachin Chitta 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)
- Reinforcement Learning: An Introduction
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- GENERATIVE ADVERSARIAL NETS
- Human-level control through deep reinforcement learning
Their papers
- Skill learning and task outcome prediction for manipulation (2011) — 235 citations
- Learning grounded finite-state representations from unstructured demonstrations (2015) — 228 citations
- STOMP: Stochastic trajectory optimization for motion planning (2011) — 1,015 citations
- Incremental Semantically Grounded Learning from Demonstration (2013) — 135 citations
- E-Graphs: Bootstrapping Planning with Experience Graphs (2012) — 108 citations
- Search-based planning for manipulation with motion primitives (2010) — 185 citations
- Reducing the Barrier to Entry of Complex Robotic Software: a MoveIt! Case Study (2014) — 568 citations
- MoveIt! [ROS Topics] (2012) — 452 citations
- FCL: A general purpose library for collision and proximity queries (2012) — 610 citations
- Human-Inspired Robotic Grasp Control With Tactile Sensing (2011) — 444 citations
- Autonomous door opening and plugging in with a personal robot (2010) — 203 citations