James C. Costello
Molecular Biology · 2012–2018
A researcher in the Science corpus: 4 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 111 citations into it
- Artificial Intelligence — 31 citations into it
- Computational Theory and Mathematics — 29 citations into it
- Statistics and Probability — 13 citations into it
- Computer Vision and Pattern Recognition — 10 citations into it
- Statistical Learning Theory — 9 citations into it
- Evaluation & Benchmarks — 8 citations into it
- Information Systems — 5 citations into it
Whom James C. Costello trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Daniel Marbach
- Christopher K. I. Williams
- Geoffrey E. Hinton
- Robert Tibshirani
- Thomas G. Dietterich
- John Shawe-Taylor
- Alex Krizhevsky
- Trevor J. Hastie
- David Ruppert
- Jonathon Shlens
Who trusts James C. Costello overall
Papers from James C. Costello's perspective
Ordered by how strongly the researchers James C. Costello 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
- Regression Shrinkage and Selection via the Lasso
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Next-Generation Machine Learning for Biological Networks. (2018) — 833 citations
- Wisdom of crowds for robust gene network inference (2012) — 1,736 citations
- A community computational challenge to predict the activity of pairs of compounds (2014) — 306 citations
- A community effort to assess and improve drug sensitivity prediction algorithms (2014) — 728 citations