161 citations · 1k across the 69 of their papers we have counts for
4 papers · 1 filter
Identifiability Guarantees for Causal Disentanglement from Soft Interventions
Jiaqi Zhang, Chandler Squires, Kristjan Greenewald +3
Causal disentanglement aims to uncover a representation of data using latent variables that are interrelated through a causal model. Such a representation is identifiable if the la…
Positivity in Linear Gaussian Structural Equation Models
Asad Lodhia, Jan-Christian Hütter, Caroline Uhler +1
We study a notion of positivity of Gaussian directed acyclic graphical models corresponding to a non-negativity constraint on the coefficients of the associated structural equation…
Unpaired Multi-Domain Causal Representation Learning
Nils Sturma, Chandler Squires, Mathias Drton +1
The goal of causal representation learning is to find a representation of data that consists of causally related latent variables. We consider a setup where one has access to data…
Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation
Wengong Jin, Siranush Sarkizova, Xun Chen +2
Protein-ligand binding prediction is a fundamental problem in AI-driven drug discovery. Prior work focused on supervised learning methods using a large set of binding affinity data…