Sudeep Dasari
Computer Vision and Pattern Recognition · 2018–2025
A researcher in the Science corpus: 10 papers; trusts 582 researchers and is trusted by 27 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 232 citations into it; #7,399 of 21,575 by trust here, #4,807 by citations
- Artificial Intelligence — 227 citations into it; #6,690 of 35,345 by trust here, #4,063 by citations
- Control and Systems Engineering — 153 citations into it; #3,156 of 8,257 by trust here, #305 by citations
- Reinforcement Learning — 135 citations into it; #684 of 2,242 by trust here, #585 by citations
- Robotics & Control — 79 citations into it; #170 of 609 by trust here, #85 by citations
- Representation & Self-Supervised Learning — 42 citations into it
- Biomedical Engineering — 36 citations into it
- Aerospace Engineering — 29 citations into it
Whom Sudeep Dasari trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Chelsea Finn
- Sergey Levine
- Pieter Abbeel
- Kaiming He
- Geoffrey E. Hinton
- Ilya Sutskever
- Diederik P. Kingma
- Alex Krizhevsky
- Yoshua Bengio
- J. Urgen Schmidhuber
Who trusts Sudeep Dasari overall
- Chelsea Finn
- Suraj Nair
- Sergey Levine
- Frederik D. Ebert
- Zipeng Fu
- Mohit Shridhar
- Nur Muhammad (Mahi) Shafiullah
- Ankit Goyal
- Yunfan Jiang
- Tony Zhao
Papers from Sudeep Dasari's perspective
Ordered by how strongly the researchers Sudeep Dasari 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- 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)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- RoboNet: Large-Scale Multi-Robot Learning (2019) — 437 citations
- One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning (2018) — 385 citations
- Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control (2018) — 474 citations
- Transformers for One-Shot Visual Imitation (2020) — 111 citations
- DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset (2024) — 905 citations
- Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration0 (2023) — 1,105 citations
- Octo: An Open-Source Generalist Robot Policy (2024) — 1,572 citations
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities (2025) — 3,609 citations
- Gemini Robotics: Bringing AI into the Physical World (2025) — 385 citations
- Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning (2018) — 67 citations