Johan Pensar

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it
• Probabilistic & Bayesian Methods — 10 citations into it
• Statistics and Probability — 6 citations into it

Whom Johan Pensar trusts overall

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

1. Jack Kuipers
2. David Maxwell Chickering
3. Dan Geiger
4. Nir Friedman
5. Giusi Moffa
6. David E. Heckerman
7. David Madigan

Papers from Johan Pensar's perspective

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

1. Bayesian Graphical Models for Discrete Data
2. Optimal Structure Identification With Greedy Search
3. Exact Bayesian Structure Discovery in Bayesian Networks (Journal of machine learning research)
4. Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks
5. Learning Gaussian Networks
6. Bayesian network learning with cutting planes
7. Partition MCMC for Inference on Acyclic Digraphs
8. Parameter Priors for Directed Acyclic Graphical Models and the Characteriration of Several Probability Distributions
9. Addendum on the scoring of Gaussian directed acyclic graphical models
10. Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning

Their papers

• Towards Scalable Bayesian Learning of Causal DAGs (2020) — 46 citations