Kumardeep Chaudhary
Molecular Biology · 2013–2017
A researcher in the Science corpus: 5 papers; trusts 12 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 52 citations into it
- Artificial Intelligence — 8 citations into it
Whom Kumardeep Chaudhary trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Peter J. Rousseeuw
- Jerome H. Friedman
- Bo Wang
- Robert Tibshirani
- Mathieu Bastian
- Pan Du
- Trevor J. Hastie
- Michael I. Love
- Christof Angermueller
Who trusts Kumardeep Chaudhary overall
- Nimrod Rappoport
- Ken Asada
- Wan Zhu
- Alexandr A Kalinin
- Satoshi Takahashi
- Ryuji Hamamoto
- Milan Picard
- Ron Shamir
- Kazuma Kobayashi
- Longxiang Xie
Papers from Kumardeep Chaudhary's perspective
Ordered by how strongly the researchers Kumardeep Chaudhary trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
Their papers
- More Is Better: Recent Progress in Multi-Omics Data Integration Methods (2017) — 616 citations
- CPPsite 2.0: a repository of experimentally validated cell-penetrating peptides (2015) — 301 citations
- In Silico Approach for Predicting Toxicity of Peptides and Proteins (2013) — 1,721 citations
- Deep Learning based multi-omics integration robustly predicts survival in liver cancer (2017) — 858 citations
- In Silico Models for Designing and Discovering Novel Anticancer Peptides (2013) — 297 citations