Gabrielle Gauthier Melançon

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 59 citations into it
• Probabilistic & Bayesian Methods — 23 citations into it

Whom Gabrielle Gauthier Melançon trusts overall

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

1. Radford M. Neal

Papers from Gabrielle Gauthier Melançon's perspective

Ordered by how strongly the researchers Gabrielle Gauthier Melançon 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. Gradient-based learning applied to document recognition
4. Pattern Recognition and Machine Learning
5. Learning Multiple Layers of Features from Tiny Images
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Bayesian learning for neural networks
8. Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
9. Long Short-Term Memory
10. ImageNet: A large-scale hierarchical image database

Their papers

• Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty (2020) — 336 citations