Philip Pilgerstorfer

International Conference on Artificial Intelligence and Statistics · 2020

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

Whom Philip Pilgerstorfer trusts overall

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

1. David Maxwell Chickering

Papers from Philip Pilgerstorfer's perspective

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

1. Optimal Structure Identification With Greedy Search
2. Learning Bayesian networks: The combination of knowledge and statistical data
3. A Linear Non-Gaussian Acyclic Model for Causal Discovery
4. Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning
5. Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity
6. Emergence of Scaling in Random Networks
7. Searching for the Causal Structure of a Vector Autoregression
8. Numerical optimization
9. Learning high-dimensional directed acyclic graphs with latent and selection variables
10. Identifiability of Gaussian structural equation models with equal error variances

Their papers

• DYNOTEARS: Structure Learning from Time-Series Data (2020) — 311 citations