Chris Lucas

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 7 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it

Whom Chris Lucas trusts overall

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

1. Radford M. Neal

Papers from Chris Lucas's perspective

Ordered by how strongly the researchers Chris Lucas trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Dropout: a simple way to prevent neural networks from overfitting
3. MADE: Masked Autoencoder for Distribution Estimation
4. Annealed importance sampling
5. Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning
6. Multilayer feedforward networks are universal approximators
7. Neural Adaptive Sequential Monte Carlo
8. Amortized Inference in Probabilistic Reasoning
9. Inference Networks for Sequential Monte Carlo in Graphical Models
10. Recognition Networks for Approximate Inference in BN20 Networks

Their papers

• A Universal Marginalizer for Amortized Inference in Generative Models (2017) — 31 citations