51 Open source projects that are alternatives of or similar to ncem

Convert between AnnData and SingleCellExperiment

Causing: CAUsal INterpretation using Graphs

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

Conditional out-of-distribution prediction

A Deep Graph Neural Network Architecture for Modelling Spatio-temporal Dynamics in rs-fMRI Data

Code and resources on scalable and efficient Graph Neural Networks

LIANA: a LIgand-receptor ANalysis frAmework

Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.

Voxel generator based on perlin 3d noise | Python OpenGL

Code for reproducing results in GraphMix paper

R package to do the Ligand Receptor Analysis Visualization

Fast OpenGL Mathematics (GLM) for Python

Personal repo for learning the vulkan graphics api

bigg (bgfx + imgui + glfw + glm) + utils

C++ tools for gamedev based on SDL2 and OpenGL

Efficient Fitting of Linear and Generalized Linear Models by using just base R. The speed gains over lm and glm are obtained by reducing the NxP model matrix to a PxP matrix, and the best computational performance is obtained when R is linked against OpenBLAS, Intel MKL or other optimized BLAS library.

R package that provides estimation methods for Gravity Models

Brandon Pelfrey's SPH fluid simulation tutorial

Estimation and inference from generalized linear models using explicit and implicit methods for bias reduction

OpenGL Mathematics (GLM)

ARehab is a free software for physical rehab, aided by augmented reality technologies and user tracking systems, such as Microsoft Kinect v2.

💀 A skeleton OpenGL C++ app bootstrapped with glfw, glad, and glm.

Download and process GOES-16 and GOES-17 data from NOAA's archive on AWS using Python.

🌋🌱 A Vulkan starter repo that you could use to get the ball rolling.

Code for the General Lake Model

Faster, better, smarter ecological niche modeling and species distribution modeling

Collection of generative models in Tensorflow

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

Noise removal from images using Convolutional autoencoder

Its a social networking chat-bot trained on Reddit dataset . It supports open bounded queries developed on the concept of Neural Machine Translation. Beware of its being sarcastic just like its creator 😝 BDW it uses Pytorch framework and Python3.

Invariant representation learning from imaging and spectral data

Must-read papers on graph neural networks (GNN)

TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

[CVPR 2020 VL3] The repository for meta fine-tuning in cross-domain few-shot learning.

GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)

A reading list for deep graph learning acceleration.

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

Pytorch implementation of CVPR2020 paper “VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation”

The official PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf '21)

STAGIN: Spatio-Temporal Attention Graph Isomorphism Network

Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022

List of Publications in Graph Contrastive Learning

A real-time GNN-based method. Understanding Image Retrieval Re-Ranking: A Graph Neural Network Perspective

An index of recommendation algorithms that are based on Graph Neural Networks.

This shows a basic implementation of the global nearest neighbour (GNN) multi target Tracker. Kalman filter is used for Tracking and Auction Algorithm for determining the assignment of measurments to filters.

A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).

Clean & Documented TF2 implementation of "An end-to-end deep learning architecture for graph classification" (M. Zhang et al., 2018).

A Pytorch implementation of CVPR 2020 paper: Multi-Modal Graph Neural Network for Joint Reasoning on Vision and Scene Text

characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomics data with nonuniform cellular densities

Spatial Single Cell Analysis in Python