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stat.ML2026
Causal ASCEND: Scalable Two-tier Causal Discovery on High Dimensional Multi-omics Data
Stephen Asiedu, David Watson
Biological systems exhibit a hierarchical structure, characterised by directed flow from upstream regulators to downstream effects. Although this ordering provides a natural scaffo…
stat.ML2026
Minimax Rates and Spectral Distillation for Tree Ensembles
Binh Duc Vu, David S. Watson
Tree ensembles such as random forests (RFs) and gradient boosting machines (GBMs) are among the most widely used supervised learners, yet their theoretical properties remain incomp…
stat.ML2025
Autoencoding Random Forests
Binh Duc Vu, Jan Kapar, Marvin Wright +1
We propose a principled method for autoencoding with random forests. Our strategy builds on foundational results from nonparametric statistics and spectral graph theory to learn a…