Nishanth Kumar

Artificial Intelligence · 2019–2022

A researcher in the Science corpus: 2 papers; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 41 citations into it
• Reinforcement Learning — 30 citations into it
• Control and Systems Engineering — 17 citations into it
• Computer Vision and Pattern Recognition — 16 citations into it

Whom Nishanth Kumar trusts overall

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

1. Diederik P. Kingma
2. Sergey Levine
3. Pieter Abbeel
4. Richard S. Sutton
5. Malte Helmert
6. Geoffrey E. Hinton
7. Andrew Barto
8. Chelsea Finn
9. Blai Bonet
10. George Dimitri Konidaris

Papers from Nishanth Kumar's perspective

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

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

Their papers

• Inventing Relational State and Action Abstractions for Effective and Efficient Bilevel Planning (2022) — 19 citations
• Learning Deep Parameterized Skills from Demonstration for Re-targetable Visuomotor Control (2019) — 11 citations