Nitesh Choubey

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 44 citations into it
• Probabilistic & Bayesian Methods — 31 citations into it
• Statistics and Probability — 24 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Statistical Learning Theory — 17 citations into it
• Management Science and Operations Research — 9 citations into it

Whom Nitesh Choubey trusts overall

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

1. Radford M. Neal
2. Bernhard Schölkopf
3. Geoffrey E. Hinton
4. David John Cameron MacKay
5. Alex Smola
6. Jim Hefferon
7. Diederik P. Kingma

Papers from Nitesh Choubey's perspective

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

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

Their papers

• Mathematics for Machine Learning (2020)