Mayank Bansal

Computer Vision and Pattern Recognition · 2012–2019

A researcher in the Science corpus: 3 papers; trusts 126 researchers and is trusted by 25 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 32 citations into it; #14,203 of 21,575 by trust here, #10,334 by citations
• Artificial Intelligence — 26 citations into it; #9,372 of 35,345 by trust here, #9,641 by citations
• Automotive Engineering — 20 citations into it; #253 of 3,081 by trust here, #849 by citations
• Reinforcement Learning — 14 citations into it
• Control and Systems Engineering — 8 citations into it
• Robotics & Control — 7 citations into it
• Safety, Robustness & Interpretability — 5 citations into it

Whom Mayank Bansal trusts overall

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

1. Alexey Dosovitskiy
2. Jana Kosecka
3. Jean-Philippe Tardif
4. Kaiming He
5. Wenjie Luo
6. Alex Krizhevsky
7. Geoffrey E. Hinton
8. Eli Shechtman
9. Radford M. Neal
10. Matthias Müller

Who trusts Mayank Bansal overall

1. François Chollet
2. Pranav Singh Chib
3. Yicong Tian
4. Zikang Zhou
5. Tung Phan-Minh
6. Thibault Buhet
7. Kashyap Chitta
8. Yuning Chai
9. Maryam Zare
10. Ruohan Wang

Papers from Mayank Bansal's perspective

Ordered by how strongly the researchers Mayank Bansal 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction (2019) — 841 citations
• ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst (2018) — 871 citations
• Ultra-wide Baseline Facade Matching for Geo-localization (2012) — 63 citations