Daniel Malinsky

Artificial Intelligence · with Hansen · 2018

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 11 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Daniel Malinsky trusts overall

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

1. Jiji Zhang
2. Vanessa Didelez
3. Alexander Sokol
4. Niels Richard Hansen
5. Søren Wengel Mogensen
6. Thomas S. Richardson
7. Tom L. Burr
8. R. Ali

Papers from Daniel Malinsky's perspective

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

1. Causation, Prediction, and Search
2. On the completeness of orientation rules for causal discovery in the presence of latent confounders and selection bias
3. MARKOV EQUIVALENCE FOR ANCESTRAL GRAPHS
4. Learning Sparse Causal Models is not NP-hard
5. Learning high-dimensional directed acyclic graphs with latent and selection variables
6. Continuous Time Bayesian Networks (Conference on Uncertainty in Artificial Intelligence)
7. Learning Causal Structure from Undersampled Time Series
8. Graphical models for marked point processes based on local independence
9. A Discovery Algorithm for Directed Cyclic Graphs
10. From Deterministic ODEs to Dynamic Structural Causal Models

Their papers

• Causal Learning for Partially Observed Stochastic Dynamical Systems (2018) — 42 citations