Jilles Vreeken

Causal Discovery from Interval-Based Event Sequences AAAI 2026 SEQRET: Mining Rule Sets from Event Sequences AAAI 2026 Federated Binary Matrix Factorization Using Proximal Optimization AAAI 2025 From Your Block to Our Block: How to Find Shared Structure Between Stochastic Block Models over Multiple Graphs AAAI 2025 Information-Theoretic Causal Discovery in Topological Order AISTATS 2025 SPACETIME: Causal Discovery from Non-Stationary Time Series AAAI 2025 Causal Discovery from Event Sequences by Local Cause-Effect Attribution NeurIPS 2024 Discovering Sequential Patterns with Predictable Inter-event Delays AAAI 2024 Finding Interpretable Class-Specific Patterns through Efficient Neural Search AAAI 2024 Identifying Confounding from Causal Mechanism Shifts AISTATS 2024 Learning Exceptional Subgroups by End-to-End Maximizing KL-Divergence ICML 2024 What Are the Rules? Discovering Constraints from Data AAAI 2024 Causal Discovery with Hidden Confounders using the Algorithmic Markov Condition UAI 2023 Federated Learning from Small Datasets ICLR 2023 Identifying Selection Bias from Observational Data AAAI 2023 Information-Theoretic Causal Discovery and Intervention Detection over Multiple Environments AAAI 2023 Learning Causal Models under Independent Changes NeurIPS 2023 Nonlinear Causal Discovery with Latent Confounders ICML 2023 Nothing but Regrets — Privacy-Preserving Federated Causal Discovery AISTATS 2023 Towards Concept-Aware Large Language Models EMNLP 2023 Differentially Describing Groups of Graphs AAAI 2022 Discovering Interpretable Data-to-Sequence Generators AAAI 2022 Efficiently Factorizing Boolean Matrices using Proximal Gradient Descent NeurIPS 2022 Inferring Cause and Effect in the Presence of Heteroscedastic Noise ICML 2022 Label-Descriptive Patterns and Their Application to Characterizing Classification Errors ICML 2022 Naming the Most Anomalous Cluster in Hilbert Space for Structures with Attribute Information AAAI 2022 Discovering Fully Oriented Causal Networks AAAI 2021 What’s in the Box? Exploring the Inner Life of Neural Networks with Robust Rules ICML 2021 Explainable Data Decompositions AAAI 2020 Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms IJCAI 2019 Testing Conditional Independence on Discrete Data using Stochastic Complexity AISTATS 2019 Multivariate Maximal Correlation Analysis ICML 2014