Scholar
Sara Magliacane
Google Scholar ID: H3j_zQ4AAAAJ
University of Amsterdam
Causality
Causal Discovery
Statistical relational learning
Probabilistic logics
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Citations & Impact
All-time
Citations
1,467
H-index
15
i10-index
20
Publications
20
Co-authors
69
list available
Contact
Email
s DOT magliacane AT uva DOT nl
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Publications
9 items
Learning Interactive World Model for Object-Centric Reinforcement Learning
2025
Cited
0
Local Causal Discovery for Statistically Efficient Causal Inference
2025
Cited
0
Challenges in Statistics: A Dozen Challenges in Causality and Causal Inference
2025
Cited
0
Finite sample-optimal adjustment sets in linear Gaussian causal models
2025
Cited
0
Combining Causal Models for More Accurate Abstractions of Neural Networks
2025
Cited
0
Learning to Defer for Causal Discovery with Imperfect Experts
2025
Cited
0
SNAP: Sequential Non-Ancestor Pruning for Targeted Causal Effect Estimation With an Unknown Graph
2025
Cited
0
Sample-efficient Learning of Concepts with Theoretical Guarantees: from Data to Concepts without Interventions
2025
Cited
0
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Resume (English only)
Background
Assistant Professor at the Amsterdam Machine Learning Lab, University of Amsterdam
ELLIS Scholar in the Interactive Learning and Interventional Representations program
Research at the intersection of causality and machine learning
Aims to improve AI robustness, generalization across domains/tasks, and safety through causal reasoning
Main research directions: causal representation learning, causal discovery, and causality-inspired ML/RL
Co-authors
69 total
Tom Claassen
Radboud University Nijmegen
Joris M. Mooij
Professor in Mathematical Statistics, Korteweg-de Vries Institute, University of Amsterdam (NL)
Efstratios Gavves
Associate Professor at University of Amsterdam
Phillip Lippe
Google DeepMind
Yuki M. Asano
Full Professor, Head of FunAI Lab, University of Technology Nuremberg
Taco Cohen
Qualcomm AI Research
Paul Groth
Professor, INDE Lab, University of Amsterdam
Thijs van Ommen
Assistant Professor at Utrecht University
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