Krishna Chaitanya Kalagarla

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 16 citations into it
• Reinforcement Learning — 13 citations into it
• Efficiency & Compression — 7 citations into it

Whom Krishna Chaitanya Kalagarla trusts overall

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

1. Andrew W. Moore
2. Geoffrey E. Hinton
3. Nicholas Frosst
4. Volodymyr Mnih
5. Pieter Abbeel
6. Stéphane Ross
7. Richard S. Sutton

Papers from Krishna Chaitanya Kalagarla's perspective

Ordered by how strongly the researchers Krishna Chaitanya Kalagarla 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. Playing Atari with Deep Reinforcement Learning (arXiv.org)
9. ImageNet: A large-scale hierarchical image database
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Designing Interpretable Approximations to Deep Reinforcement Learning with Soft Decision Trees (2020) — 10 citations