Anirudha Majumdar
Artificial Intelligence · with Pavone · 2016–2023
A researcher in the Science corpus: 4 papers; trusts 18 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 50 citations into it
- Computer Vision and Pattern Recognition — 29 citations into it; #9,742 of 21,575 by trust here, #19,310 by citations
- Control and Systems Engineering — 23 citations into it; #2,845 of 8,257 by trust here, #6,417 by citations
- Management Science and Operations Research — 20 citations into it
- Reinforcement Learning — 15 citations into it
- Statistics and Probability — 9 citations into it
- Aerospace Engineering — 8 citations into it
- Finance — 8 citations into it
Whom Anirudha Majumdar trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Andrew Y. Ng
- Pieter Abbeel
- Andrzej Ruszczynski
- Pablo A. Parrilo
- Sergey Levine
- Brian D. Ziebart
- Matthew Rabin
- James J. Kuffner Jr.
- Alexander Shapiro
- Shie Mannor
Who trusts Anirudha Majumdar overall
- Seyed Reza Ahmadzadeh
- Ya-Chien Chang
- Sonia Chernova
- Anirban Santara
- Muhammad Asif Rana
- Nima Roohi
- Daniel S. Brown
- Sicun Gao
Papers from Anirudha Majumdar's perspective
Ordered by how strongly the researchers Anirudha Majumdar 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)
- GENERATIVE ADVERSARIAL NETS
Their papers
- Funnel libraries for real-time robust feedback motion planning (2016) — 405 citations
- Risk-sensitive Inverse Reinforcement Learning via Coherent Risk Models (2017) — 72 citations
- Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners (2023) — 392 citations
- How Should a Robot Assess Risk? Towards an Axiomatic Theory of Risk in Robotics (2017) — 234 citations