Sameer Khurana

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 3 papers; trusts 30 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 53 citations into it; #30,164 of 35,345 by trust here, #21,878 by citations
• Signal Processing — 33 citations into it; #6,466 of 7,572 by trust here, #4,051 by citations
• Speech & Audio — 25 citations into it
• Computer Vision and Pattern Recognition — 19 citations into it
• Natural Language Processing — 18 citations into it
• Generative Models — 13 citations into it
• Probabilistic & Bayesian Methods — 13 citations into it

Whom Sameer Khurana trusts overall

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

1. Diederik P. Kingma
2. Alex Graves
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Alex Krizhevsky
6. Max Welling
7. Yann LeCun
8. Ilya Sutskever
9. J. Urgen Schmidhuber
10. Radford M. Neal

Who trusts Sameer Khurana overall

1. Wei-Ning Hsu
2. Lasse Borgholt
3. Jakob Drachmann Havtorn
4. David F. Harwath
5. Benjamin Bolte
6. James R. Glass

Papers from Sameer Khurana's perspective

Ordered by how strongly the researchers Sameer Khurana 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning (2020) — 29 citations
• A Factorial Deep Markov Model for Unsupervised Disentangled Representation Learning from Speech (2019) — 16 citations
• Unsupervised Domain Adaptation for Speech Recognition via Uncertainty Driven Self-Training (2020) — 74 citations