Jean-Baptiste Tristan

Artificial Intelligence · 2014

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

Subfields

• Artificial Intelligence — 8 citations into it
• Probabilistic & Bayesian Methods — 7 citations into it

Whom Jean-Baptiste Tristan trusts overall

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

1. Matthew D. Hoffman
2. David M. Blei
3. Michael I. Jordan
4. Andrew Y. Ng
5. Andrew Gelman
6. Radford M. Neal
7. Avi Pfeffer
8. T. Griffiths
9. Alex Smola
10. Geoffrey E. Hinton

Who trusts Jean-Baptiste Tristan overall

1. Vikash K. Mansinghka
2. Dustin Tran

Papers from Jean-Baptiste Tristan's perspective

Ordered by how strongly the researchers Jean-Baptiste Tristan 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. Learning Multiple Layers of Features from Tiny Images
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Attention is All you Need (Neural Information Processing Systems)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Augur: Data-Parallel Probabilistic Modeling (2014) — 29 citations