dpaysan

AdamW-pytorch

Implementation and experiments for AdamW on Pytorch

causaldag

Python package for the creation, manipulation, and learning of Causal DAGs

chuv_collaboration

cross-modal-autoencoders

dpaysan

Config files for my GitHub profile.

germinal_center

Python code for the chromatin state analyses of the paper

hsmmlearn

A library for hidden semi-Markov models with explicit durations

image2reg

Code for the paper "Image2Reg: Linking Chromatin Images to Gene Regulation using Genetic Perturbation Screens"

imageaeot

pyhsmm

Customized version of the original software package to be used for surgical activity recognition using HSMMs.

dpaysan/hsmmlearn

A library for hidden semi-Markov models with explicit durations

dpaysan/AdamW-pytorch

Implementation and experiments for AdamW on Pytorch

dpaysan/causaldag

Python package for the creation, manipulation, and learning of Causal DAGs

dpaysan/chuv_collaboration

dpaysan/cross-modal-autoencoders

dpaysan/dpaysan

Config files for my GitHub profile.

dpaysan/germinal_center

Python code for the chromatin state analyses of the paper

dpaysan/image2reg

Code for the paper "Image2Reg: Linking Chromatin Images to Gene Regulation using Genetic Perturbation Screens"

dpaysan/imageaeot

dpaysan/pyhsmm

Customized version of the original software package to be used for surgical activity recognition using HSMMs.

dpaysan/Intro2ML

Code of the projects of the Introduction to Machine Learning course 2019 at ETHZ.

dpaysan/jump_datasets

Images and other data from the JUMP Cell Painting Consortium

dpaysan/material

Material for course STA426 at UZH, Fall Semester 2020

dpaysan/NMCO-Image-Features

Nuclear Morphology and Chromatin Organization Features

dpaysan/node2vec_stability

dpaysan/pybasicbayes

Custom version of the pybasicbayes package edited to be used in the context of surgical activity recognition using HSMMs.

dpaysan/pySCENIC

pySCENIC is a lightning-fast python implementation of the SCENIC pipeline (Single-Cell rEgulatory Network Inference and Clustering) which enables biologists to infer transcription factors, gene regulatory networks and cell types from single-cell RNA-seq data.

dpaysan/scvae

Deep learning for single-cell transcript counts

dpaysan/SimpleITK-Notebooks

Jupyter notebooks for learning how to use SimpleITK

dpaysan/ST-Net

Deep learning on histopathology images.

dpaysan/sta426dp

Repository for the course work of the module STA426DP

dpaysan/unet-nuclei

Segmentation of fluorescently labelled nuclei using a pre-trained Unet

dpaysan/unet_nuclei_segmentation