Romain Lopez
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<u>Romain Lopez</u>
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Toward the Identifiability of Comparative Deep Generative Models
Multi-ContrastiveVAE disentangles perturbation effects in single cell images from optical pooled screens
Sequential optimal experimental design of perturbation screens guided by multi-modal priors
A Supervised Contrastive Framework for Learning Disentangled Representations of Cell Perturbation Data
Generative Flow Networks Assisted Biological Sequence Editing
Learning causal representations of single cells via sparse mechanism shift modeling
NODAGS-Flow: Nonlinear cyclic causal structure learning
The scverse project provides a computational ecosystem for single-cell omics data analysis
An empirical Bayes method for differential expression analysis of single cells with deep generative models
Disentangling shared and group-specific variations in single-cell transcriptomics data with multiGroupVI
Large-scale differentiable causal discovery of factor graphs
DestVI identifies continuums of cell types in spatial transcriptomics data
A Python library for probabilistic analysis of single-cell omics data
Reconstructing unobserved cellular states from paired single-cell lineage tracing and transcriptomics data
Charting Cellular States, One Cell at a Time: Computational, Inferential and Modeling Perspectives
Joint probabilistic modeling of single-cell multi-omic data with totalVI
Learning from eXtreme bandit feedback
Probabilistic harmonization and annotation of single-cell transcriptomics data with deep generative models
Decision-making with auto-encoding variational Bayes
Enhancing scientific discoveries in molecular biology with deep generative models
Cost-effective incentive allocation via structured counterfactual inference
A joint model of RNA expression and surface protein abundance in single cells
A joint model of unpaired data from scRNA-seq and spatial transcriptomics for imputing missing gene expression measurements
Deep generative models for detecting differential expression in single cells
Detecting zero-inflated genes in single-cell transcriptomics data
Scrublet: computational identification of cell doublets in single-cell transcriptomic data
Deep generative modeling for single-cell transcriptomics
Information constraints on auto-encoding variational Bayes
A deep generative model for semi-supervised classification with noisy labels
A deep generative model for gene expression profiles from single-cell RNA sequencing with application to differential expression
A deep generative model for gene expression profiles from single-cell RNA sequencing
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