93 citations · 215 across the 10 of their papers we have counts for
11 papers
NODAGS-Flow: Nonlinear Cyclic Causal Structure Learning
Muralikrishnna G. Sethuraman, Romain Lopez, Rahul Mohan +3
Learning causal relationships between variables is a well-studied problem in statistics, with many important applications in science. However, modeling real-world systems remain ch…
Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling
Romain Lopez, Nataša Tagasovska, Stephen Ra +3
Latent variable models such as the Variational Auto-Encoder (VAE) have become a go-to tool for analyzing biological data, especially in the field of single-cell genomics. One remai…
Large-Scale Differentiable Causal Discovery of Factor Graphs
Romain Lopez, Jan-Christian Hütter, Jonathan K. Pritchard +1
A common theme in causal inference is learning causal relationships between observed variables, also known as causal discovery. This is usually a daunting task, given the large num…
Learning from eXtreme Bandit Feedback
Romain Lopez, Inderjit S. Dhillon, Michael I. Jordan
We study the problem of batch learning from bandit feedback in the setting of extremely large action spaces. Learning from extreme bandit feedback is ubiquitous in recommendation s…
Decision-Making with Auto-Encoding Variational Bayes
Romain Lopez, Pierre Boyeau, Nir Yosef +2
To make decisions based on a model fit with auto-encoding variational Bayes (AEVB), practitioners often let the variational distribution serve as a surrogate for the posterior dist…
A joint model of unpaired data from scRNA-seq and spatial transcriptomics for imputing missing gene expression measurements
Romain Lopez, Achille Nazaret, Maxime Langevin +4
Spatial studies of transcriptome provide biologists with gene expression maps of heterogeneous and complex tissues. However, most experimental protocols for spatial transcriptomics…