1 citations · 1 across the 2 of their papers we have counts for
3 papers
stat.ML2026
Deep and Probabilistic Models for Gene Regulatory Network Inference
Claudia Skok Gibbs
Gene regulatory networks (GRNs) link transcription factor (TF) proteins to their target genes, yet reconstructing these networks from genome-wide data remains challenging under pra…
cs.AI2026★ 1 cited
MIMIC: A Generative Multimodal Foundation Model for Biomolecules
Siavash Golkar, Jake Kovalic, Irina Espejo Morales +28
Biological function emerges from coupled constraints across sequence, structure, regulation, evolution, and cellular context, yet most foundation models in biology are trained with…
cs.LG2025
Large-Scale Targeted Cause Discovery via Learning from Simulated Data
Jang-Hyun Kim, Claudia Skok Gibbs, Sangdoo Yun +2
We propose a novel machine learning approach for inferring causal variables of a target variable from observations. Our focus is on directly inferring a set of causal factors witho…