4 citations · 5 across the 13 of their papers we have counts for
4 papers · 1 filter
Causal Structure and Representation Learning with Biomedical Applications
Caroline Uhler, Jiaqi Zhang
Massive data collection holds the promise of a better understanding of complex phenomena and, ultimately, better decisions. Representation learning has become a key driver of deep…
Probabilistic Factorial Experimental Design for Combinatorial Interventions
Divya Shyamal, Jiaqi Zhang, Caroline Uhler
A combinatorial intervention, consisting of multiple treatments applied to a single unit with potentially interactive effects, has substantial applications in fields such as biomed…
Meta-Dependence in Conditional Independence Testing
Bijan Mazaheri, Jiaqi Zhang, Caroline Uhler
Conditional independence testing is a critical component of feature screening, invariant statistical models, and causal discovery. Many of these algorithms rely on the sequential a…
No Foundations without Foundations -- Why semi-mechanistic models are essential for regulatory biology
Luka Kovačević, Thomas Gaudelet, James Opzoomer +5
Despite substantial efforts, deep learning has not yet delivered a transformative impact on elucidating regulatory biology, particularly in the realm of predicting gene expression…