Jay Baxter

Artificial Intelligence · 2015

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 — 7 citations into it
• Statistics and Probability — 5 citations into it

Whom Jay Baxter trusts overall

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

1. Radford M. Neal
2. Carl E. Rasmussen

Papers from Jay Baxter's perspective

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

1. Probabilistic reasoning in intelligent systems: Networks of plausible inference
2. Markov Chain Sampling Methods for Dirichlet Process Mixture Models
3. Generalized Linear Models
4. Spark: Cluster Computing with Working Sets
5. Bayesian data analysis.
6. MLbase: A Distributed Machine-learning System
7. BLOG: Probabilistic Models with Unknown Objects
8. Church: a language for generative models
9. Sequential Monte Carlo Methods in Practice
10. The Infinite Gaussian Mixture Model

Their papers

• BayesDB: A probabilistic programming system for querying the probable implications of data (2015) — 39 citations