Mudit Verma

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 39 citations into it
• Reinforcement Learning — 31 citations into it
• Control and Systems Engineering — 10 citations into it

Whom Mudit Verma trusts overall

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

1. W. B. Knox
2. Yann LeCun
3. Ruohan Zhang
4. Richard S. Sutton
5. Geoffrey E. Hinton
6. Yoshua Bengio
7. Peter Stone
8. Andrew Y. Ng
9. Diederik P. Kingma
10. Alex Krizhevsky

Papers from Mudit Verma's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Human-level control through deep reinforcement learning
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Symbols as a Lingua Franca for Bridging Human-AI Chasm for Explainable and Advisable AI Systems (2021) — 56 citations
• Widening the Pipeline in Human-Guided Reinforcement Learning with Explanation and Context-Aware Data Augmentation (2020) — 56 citations