hlpureboy

StableDiffusionReconstruction

Takagi and Nishimoto, CVPR 2023

Diffusion-Models-pytorch

Pytorch implementation of Diffusion Models (https://arxiv.org/pdf/2006.11239.pdf)

FocalNet

[NeurIPS 2022] Official code for "Focal Modulation Networks"

benchmark_VAE

Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

BioGPT

IOPaint

Image inpainting tool powered by SOTA AI Model. Remove any unwanted object, defect, people from your pictures or erase and replace(powered by stable diffusion) any thing on your pictures.

explainerdashboard

Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

ukbb-cca

Canonical Correlation Analysis on behavioural and brain imaging data from the UK Biobank

Imaging-transcriptomics

A package, and script, to perform imaging transcriptomics on a neuroimaging scan.

segmentation_models.pytorch

Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

stable-diffusion-webui

Stable Diffusion web UI

BigFLICA

brainchop

Brainchop: In-browser 3D MRI rendering and segmentation

macapype

PNH segmentation pipelines based on nipype

CortexODE

The official implementation of CortexODE

stable-diffusion

A latent text-to-image diffusion model

NeuroKit

NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing

GNNs-in-Network-Neuroscience

A review of papers proposing novel GNN methods with application to brain connectivity published in 2017-2020.

CLIP

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

DeepPurpose

A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)

neuroparc

awesome-contrastive-self-supervised-learning

A comprehensive list of awesome contrastive self-supervised learning papers.

pylustrator

Visualisations of data are at the core of every publication of scientific research results. They have to be as clear as possible to facilitate the communication of research. As data can have different formats and shapes, the visualisations often have to be adapted to reflect the data as well as possible. We developed Pylustrator, an interface to directly edit python generated matplotlib graphs to finalize them for publication. Therefore, subplots can be resized and dragged around by the mouse, text and annotations can be added. The changes can be saved to the initial plot file as python code.

Contrastive-Predictive-Coding-PyTorch

Contrastive Predictive Coding for Automatic Speaker Verification

IJCAI2023-CoNR

IJCAI2023 - Collaborative Neural Rendering using Anime Character Sheets

SimCLR

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

awesome-self-supervised-learning

A curated list of awesome self-supervised methods

scikit-learn

scikit-learn: machine learning in Python

RadiomicsFeatureVisualization

Visualization for radiomics feature generated by pyradiomics

networkx

Network Analysis in Python