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stat.ML2026
Estimating Treatment Effects with Independent Component Analysis
Patrik Reizinger, Lester Mackey, Wieland Brendel +1
Independent Component Analysis (ICA) uses a measure of non-Gaussianity to identify latent sources from data and estimate their mixing coefficients (Shimizu et al., 2006). Meanwhile…
stat.ML2025
Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning
Patrik Reizinger, Siyuan Guo, Ferenc Huszár +2
Identifying latent representations or causal structures is important for good generalization and downstream task performance. However, both fields have been developed rather indepe…
stat.ML2024
Position: Understanding LLMs Requires More Than Statistical Generalization
Patrik Reizinger, Szilvia Ujváry, Anna Mészáros +3
The last decade has seen blossoming research in deep learning theory attempting to answer, "Why does deep learning generalize?" A powerful shift in perspective precipitated this pr…