Pierre Boyeau

Pierre Boyeau

University of California, Berkeley

H-index: 8

North America-United States

About Pierre Boyeau

Pierre Boyeau, With an exceptional h-index of 8 and a recent h-index of 8 (since 2020), a distinguished researcher at University of California, Berkeley,

His recent articles reflect a diverse array of research interests and contributions to the field:

AutoEval Done Right: Using Synthetic Data for Model Evaluation

Calibrated Identification of Feature Dependencies in Single-cell Multiomics

CherryML: scalable maximum likelihood estimation of phylogenetic models

Predicting cellular responses to complex perturbations in high‐throughput screens

An empirical Bayes method for differential expression analysis of single cells with deep generative models

Deep generative modeling for quantifying sample-level heterogeneity in single-cell omics

DestVI identifies continuums of cell types in spatial transcriptomics data

A Python library for probabilistic analysis of single-cell omics data

Pierre Boyeau Information

University

Position

___

Citations(all)

426

Citations(since 2020)

426

Cited By

10

hIndex(all)

8

hIndex(since 2020)

8

i10Index(all)

8

i10Index(since 2020)

8

Email

University Profile Page

Google Scholar

Top articles of Pierre Boyeau

AutoEval Done Right: Using Synthetic Data for Model Evaluation

arXiv preprint arXiv:2403.07008

2024/3/9

Pierre Boyeau
Pierre Boyeau

H-Index: 2

Jitendra Malik
Jitendra Malik

H-Index: 104

Calibrated Identification of Feature Dependencies in Single-cell Multiomics

bioRxiv

2023/11/5

Pierre Boyeau
Pierre Boyeau

H-Index: 2

Stephen Bates
Stephen Bates

H-Index: 7

CherryML: scalable maximum likelihood estimation of phylogenetic models

Nature methods

2023/8

Predicting cellular responses to complex perturbations in high‐throughput screens

Molecular systems biology

2023/6/12

An empirical Bayes method for differential expression analysis of single cells with deep generative models

Proceedings of the National Academy of Sciences

2023

Deep generative modeling for quantifying sample-level heterogeneity in single-cell omics

BioRxiv

2022/10/6

DestVI identifies continuums of cell types in spatial transcriptomics data

Nature biotechnology

2022/9

Multi-resolution deconvolution of spatial transcriptomics data reveals continuous patterns of inflammation

BioRxiv

2021/5/11

Decision-making with auto-encoding variational Bayes

2020/12

See List of Professors in Pierre Boyeau University(University of California, Berkeley)