← Authors

Tom Claassen

17 papers · 2010–2025 · 7 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (15) 🐝 Cross-Pollinator (8) 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (15) 🧬 Topic Evolution πŸ”¬ Deep Specialist (12) πŸ† Keyword Champion (3) πŸ“ˆ Trend Setter ⚑ Prolific Year (5) πŸ’Ž Century Club (17) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (58)

Conferences

NIPS (4) PGM (4) UAI (4) AISTATS (2) CLEAR (1) IJCAI (1) JMLR (1)

Top co-authors

Tom Heskes (9) Ioan Gabriel Bucur (5) Joris M. Mooij (5) Sara Magliacane (4) Mirthe Maria Van Diepen (1) Aafke M Schipper (1) Elena Sokolova (1) Evi Sijben (1) Holger H. Hoos (1) Mitra Baratchi (1)

Keywords

causal discovery (9) causal inference (5) markov equivalence (3) graphical model (3) constraint-based method (3) fci algorithm (3) causal structure (2) instrumental variable (2) faithfulness assumption (2) causal relation (2) partial ancestral graph (2) bayesian inference (2) model inference (1) directed graph (1) model interpretability (1) conditional probability (1) causal effect estimation (1) spatial structure (1) posterior inference (1) bayesian network (1)

Papers

SNAP: Sequential Non-Ancestor Pruning for Targeted Causal Effect Estimation With an Unknown Graph AISTATS 2025
AutoCD: Automated Machine Learning for Causal Discovery Algorithms PGM 2024
Beyond the Markov Equivalence Class: Extending Causal Discovery under Latent Confounding CLEAR 2023
Establishing Markov equivalence in cyclic directed graphs UAI 2023
Greedy equivalence search in the presence of latent confounders UAI 2022
Joint Causal Inference from Multiple Contexts JMLR 2020
Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models NIPS 2020
Discovering cause-effect relationships in spatial systems with a known direction based on observational data PGM 2020
MASSIVE: Tractable and Robust Bayesian Learning of Many-Dimensional Instrumental Variable Models UAI 2020
Constraint-Based Causal Discovery using Partial Ancestral Graphs in the presence of Cycles UAI 2020
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions NIPS 2018
A Bayesian Approach for Inferring Local Causal Structure in Gene Regulatory Networks PGM 2018
Robust Causal Estimation in the Large-Sample Limit without Strict Faithfulness AISTATS 2017
Computing Lower and Upper Bounds on the Probability of Causal Statements PGM 2016
Ancestral Causal Inference NIPS 2016
Bayesian Probabilities for Constraint-Based Causal Discovery IJCAI 2013
Causal discovery in multiple models from different experiments NIPS 2010