Software

On this page, you can find some details about different software packages and libraries that I have developed or contributed to.

NuCount

Machine Learning

Biology

Python

Aggregating nuclei segmentation methods to quantify cell counts in spatial transcriptomics data

funStatTest

Statistics

R

Statistical Testing for Functional Data

dual.spls

Statistics

R

Dual norm-based Sparse Partial Least Squares Regression

NIPD

Statistics

Genomics

Python

Bayesian inference for non-invasive prenatal diagnostic of genetic diseases

YALES2BIO

fluid mechanics

CI

Numerical solver for fluid mechanics

BenchOpt

Machine learning

Python

R

Julia

Benchmark repository for optimization

DIYABC-RF GUI

Machine learning

Genetics

GUI

Graphical User Interface for DYIABC-RF software

KeOps

Machine learning

Python

Matlab

R

GPU

Seamless Kernel Operations on GPU with auto-differentiation and without memory overflows

ckn-tf

Machine learning

Python

Re-implementation of Convolutional Kernel Network (CKN) from Mairal (2016) in Python based on the TensorFlow framework

Loter

Machine learning

Genetics

Python package for haplotype phasing and local ancestry inference (population genetics)

SPAMS

Machine learning

Python

Matlab

R

Optimization toolbox for sparse estimation, implementing algorithms that solve machine learning and signal processing problems involving sparse regularizations.

pCMF

Statistics

R

Genomics

Probabilistic count matrix factorization for single cell transcriptomic data analyses (dimension reduction, visualization).

plsgenomics

Statistics

R

Genomics

Supervised methods for dimension reduction in classification and regression framework (in particular PLS-based routines for genomic data analyses).