Priya Sundaresan

Computer Vision and Pattern Recognition · 2020–2023

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 69 citations into it
• Representation & Self-Supervised Learning — 6 citations into it
• Computational Mechanics — 5 citations into it

Whom Priya Sundaresan trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Gregory R. Koch
2. Ken Perlin
3. Kaiming He
4. David G. Lowe
5. Peter R. Florence
6. Tanner Schmidt
7. John E. Hopcroft
8. Paul Bao
9. Jeffrey Mahler
10. Ross B. Girshick

Who trusts Priya Sundaresan overall

1. Hang Yin

Papers from Priya Sundaresan's perspective

Ordered by how strongly the researchers Priya Sundaresan trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data (2020) — 145 citations
• Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration0 (2023) — 1,105 citations