Pratyusha Sharma
Artificial Intelligence · 2018–2022
A researcher in the Science corpus: 4 papers; trusts 291 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 79 citations into it; #30,061 of 35,345 by trust here, #13,760 by citations
- Computer Vision and Pattern Recognition — 62 citations into it; #18,442 of 21,575 by trust here, #9,435 by citations
- Reinforcement Learning — 48 citations into it; #1,985 of 2,242 by trust here, #1,545 by citations
- Natural Language Processing — 34 citations into it
- Control and Systems Engineering — 33 citations into it; #7,007 of 8,257 by trust here, #2,692 by citations
- Biomedical Engineering — 20 citations into it
- Robotics & Control — 16 citations into it; #468 of 609 by trust here, #395 by citations
- Model Architectures — 9 citations into it
Whom Pratyusha Sharma trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Krizhevsky
- Diederik P. Kingma
- Kaiming He
- Ross B. Girshick
- Yoshua Bengio
- Ilya Sutskever
- Karen Simonyan
- Richard S. Sutton
- Yann LeCun
Who trusts Pratyusha Sharma overall
Papers from Pratyusha Sharma's perspective
Ordered by how strongly the researchers Pratyusha Sharma 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)
- 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)
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Skill Induction and Planning with Latent Language (2021) — 129 citations
- Multiple Interactions Made Easy (MIME): Large Scale Demonstrations Data for Imitation (2018) — 133 citations
- Correcting Robot Plans with Natural Language Feedback (2022) — 128 citations
- Learning human–environment interactions using conformal tactile textiles (2021) — 378 citations