Python Sparse-graphs Resources

Focal Sparse Convolutional Networks for 3D Object Detection (CVPR 2022, Oral) This is the official implementation of Focals Conv (CVPR 2022), a new sp

Reconstructing Surfaces for Sparse Point Clouds with On-Surface Priors (CVPR 2022) Personal Web Pages | Paper | Project Page This repository contains

SparseInst 🚀 A simple framework for real-time instance segmentation, CVPR 2022 by Tianheng Cheng, Xinggang Wang†, Shaoyu Chen, Wenqiang Zhang, Qian Z

Structured Sparse R-CNN for Direct Scene Graph Generation Our paper Structured Sparse R-CNN for Direct Scene Graph Generation has been accepted by CVP

ipyvizzu - Jupyter notebook integration of Vizzu. Tutorial · Examples · Repository About The Project ipyvizzu is the Jupyter Notebook integration of V

SDM - Lab 1 @ UPC 👨🏻‍💻 Table of contents Introduction Property Graph Dataset 1. Introduction This repo is all about what we have done in SDM lab 1

Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences This repository is an official PyTorch implementation of Neighbor

Graph Data Science: an abstraction layer in Python for building knowledge graphs, integrated with popular graph libraries – atop Pandas, RDFlib, pySHACL, RAPIDS, NetworkX, iGraph, PyVis, pslpython, pyarrow, etc.

[ICLR 2022] The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training The Unreasonable Effectiveness of

PGMax implements general factor graphs for discrete probabilistic graphical models (PGMs), and hardware-accelerated differentiable loopy belief propagation (LBP) in JAX.

Dictionary Learning for Clustering on Hyperspectral Images Overview Framework for Spectral Clustering on the Sparse Coefficients of Learned Dictionari

Tracks how much money a profile has in their bank and graphs it, as long as they enable the bank api. (you could really use this to track anything from the hypixel api)

🔥 Olympics Data Analysis 🔥 In Data Science field, there is a big topic before creating a model for future prediction is Data Analysis. We can find o

mapomatic Automatic mapping of compiled circuits to low-noise sub-graphs Overvie

Hatchet Hatchet is a Python-based library that allows Pandas dataframes to be indexed by structured tree and graph data. It is intended for analyzing

machine-learning-with-graphs My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs Course materials can be

SPLADE 🍴 + 🥄 = 🔎 This repository contains the weights for four models as well as the code for running inference for our two papers: [v1]: SPLADE: S

Near-Optimal Sparse Allreduce for Distributed Deep Learning (published in PPoPP'22) Ok-Topk is a scheme for distributed training with sparse gradients

Sparse network learning with snlpy Very large and sparse networks appear often in the wild and present unique algorithmic opportunities and challenges

Tracking Progress in Question Answering over Knowledge Graphs Table of contents Question Answering Systems with Descriptions The QA Systems Table cont

Bootstrapped Representation Learning on Graphs This is the PyTorch implementation of BGRL Bootstrapped Representation Learning on Graphs The main scri

Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models Abstract Many applications of generative models rely on the marginali

Deep Learning on SDF for Classifying Brain Biomarkers To reproduce the results f

STonKGs STonKGs is a Sophisticated Transformer that can be jointly trained on biomedical text and knowledge graphs. This multimodal Transformer combin

Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently This repository is the official implementat

tplot is a Python package for creating text-based graphs. Useful for visualizing data to the terminal or log files.

STAR Official implementation of S parse T ransformer-based A ction R ecognition Dataset download NTU RGB+D 60 action recognition of 2D/3D skeleton fro

Scaling Vision with Sparse Mixture of Experts This repository contains the code for training and fine-tuning Sparse MoE models for vision (V-MoE) on I

Dictionary Learning with Uniform Sparse Representations for Anomaly Detection Implementation of the Uniform DL Representation for AD algorithm describ

Graph-to-3D This is the official implementation of the paper Graph-to-3d: End-to-End Generation and Manipulation of 3D Scenes Using Scene Graphs | arx

saltstatevis Just a simple python script to generate graphs of salt state requisites. Installation Requirements You will need to install graphviz to r

PYGON A Graph Neural Network Tool for Recovering Dense Sub-graphs in Random Dense Graphs. Installation This code requires to install and run the graph

MothPruning Scientific Overview Originally inspired by biological nervous systems, deep neural networks (DNNs) are powerful computational tools for mo

Plotting intersection of curves using gradient descent Webapp Link --- What's the app about Why this app Plotting functions and their intersection. A

GAT - Graph Attention Network (PyTorch) 💻 + graphs + 📣 = ❤️ This repo contains a PyTorch implementation of the original GAT paper ( 🔗 Veličković et

SG2HOI This repository is for our paper Exploiting Scene Graphs for Human-Object Interaction Detection accepted by ICCV 2021. Installation Pytorch 1.7

Learning with Noisy Labels via Sparse Regularization This repository is the official implementation of [Learning with Noisy Labels via Sparse Regulari

Block Sparse Attention 研究总结 本人近半年来对Block Sparse Attention（块稀疏注意力）的研究总结（持续更新中）。按时间顺序，主要分为如下三部分： PyTorch 自定义 CUDA 算子——以矩阵乘法为例 基于 Triton 的 Block Sparse A

Say As You Wish: Fine-grained Control of Image Caption Generation with Abstract Scene Graphs This repository contains PyTorch implementation of our pa

Glyth Graph Revision for 0.01 A simple, yet versatile, package for graphing equations on a 2-dimensional text canvas List of contents: Brief Introduct

Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetu

Organseg dags - The repository contains the codebase for multi-organ segmentation with directed acyclic graphs (DAGs) in CT.

Generalized Matrix Means for Semi-Supervised Learning with Multilayer Graphs MATLAB implementation of the paper: P. Mercado, F. Tudisco, and M. Hein,

Contrastive Multi-View Representation Learning on Graphs This work introduces a self-supervised approach based on contrastive multi-view learning to l

graphr Introduction graphr is a small language written to create basic mathematical graphs. It is an interpreted language written in python and essent

Sparse-dense operators implementation for Paddle This module implements coo, csc and csr matrix formats and their inter-ops with dense matrices. Feel

SelfTask-GNN A PyTorch implementation of "Self-supervised Learning on Graphs: Deep Insights and New Directions". [paper] In this paper, we first deepe

Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs This repository is the implementation of SELAR. Dasol Hwang* , Jinyoung Pa

Reference Code for AAAI-20 paper "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels" Please refer to htt

Mycodo Environmental Regulation System Latest version: 8.12.9 Mycodo is open source software for the Raspberry Pi that couples inputs and outputs in i

Profile and test to gain insights into the performance of your beautiful Python code View Demo - Report Bug - Request Feature QuickPotato in a nutshel

Tries to clean your dense mocap graphs like an animator would! So it will produce a usable artist friendly result while maintaining the original graph.

LynxKite is a complete graph data science platform for very large graphs and other datasets. It seamlessly combines the benefits of a friendly graphical interface and a powerful Python API.

Mega-NeRF This repository contains the code needed to train Mega-NeRF models and generate the sparse voxel octrees used by the Mega-NeRF-Dynamic viewe

taichi_LBM3D Background Taichi_LBM3D is a 3D lattice Boltzmann solver with Multi-Relaxation-Time collision scheme and sparse storage structure impleme

Flame Graphs visualize profiled code

Leaded Gradient Method (LGM) This repository contains the PyTorch implementation for paper Dynamics-aware Adversarial Attack of 3D Sparse Convolution

Neural Sparse Voxel Fields (NSVF) Project Page | Video | Paper | Data Photo-realistic free-viewpoint rendering of real-world scenes using classical co

EMLight: Lighting Estimation via Spherical Distribution Approximation (AAAI 2021) Update 12/2021: We release our Virtual Object Relighting (VOR) Datas

Multi-task Learning of Order-Consistent Causal Graphs (NeuRIPs 2021) Authors: Xinshi Chen, Haoran Sun, Caleb Ellington, Eric Xing, Le Song Link to pap

Edge-augmented Graph Transformer Introduction This is the official implementation of the Edge-augmented Graph Transformer (EGT) as described in https:

Sinkhorn Transformer This is a reproduction of the work outlined in Sparse Sinkhorn Attention, with additional enhancements. It includes a parameteriz

entmax This package provides a pytorch implementation of entmax and entmax losses: a sparse family of probability mappings and corresponding loss func

Status: Archive (code is provided as-is, no updates expected) Update August 2020: For an example repository that achieves state-of-the-art modeling pe

Sparse Physics-based and Interpretable Neural Networks for PDEs This repository contains the code and manuscript for research done on Sparse Physics-b

Hierarchical Clustering: O(1)-Approximation for Well-Clustered Graphs This repository contains code to accompany the paper "Hierarchical Clustering: O

Sparse Structure Learning via Graph Neural Networks for inductive document classification Make graph dataset create co-occurrence graph for datasets.

SST: Single-stride Sparse Transformer This is the official implementation of paper: Embracing Single Stride 3D Object Detector with Sparse Transformer

MinkLoc3D-SI: 3D LiDAR place recognition with sparse convolutions,spherical coordinates, and intensity Introduction The 3D LiDAR place recognition aim

Context-Aware-Healthcare Codes for AAAI 2022 paper: Context-aware Health Event Prediction via Transition Functions on Dynamic Disease Graphs Download

SST: Single-stride Sparse Transformer This is the official implementation of paper: Embracing Single Stride 3D Object Detector with Sparse Transformer

i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery This is a public code repository for the publication: i-SpaSP: Structured Neural Pruning

LitMatter A template for rapid experimentation and scaling deep learning models on molecular and crystal graphs. How to use Clone this repository and

SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning This repository is the official implementation of "SHRIMP: Sparser Random Featur

Augmentation-Free Self-Supervised Learning on Graphs An official source code for Augmentation-Free Self-Supervised Learning on Graphs paper, accepted

Augmentation-Free Self-Supervised Learning on Graphs An official source code for Augmentation-Free Self-Supervised Learning on Graphs paper, accepted

Reviatalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation This is the implementation of the approach describ

Mars tiler Mars Tiler is a prototype web application that serves tiles from cloud-optimized GeoTIFFs, with an emphasis on supporting planetary dataset

TREE HEIGHT EXTRACTION IN SPARSE SCENES BASED ON UAV REMOTE SENSING This is the offical python implementation of the paper "Tree Height Extraction in

ts2vg: Time series to visibility graphs The Python ts2vg package provides high-performance algorithm implementations to build visibility graphs from t

DominoSearch This is repository for codes and models of NeurIPS2021 paper - DominoSearch: Find layer-wise fine-grained N:M sparse schemes from dense n

Online Learning Of Neural Computations From Sparse Temporal Feedback This repository is the official implementation of the NeurIPS 2021 paper Online L

Deformable Butterfly: A Highly Structured and Sparse Linear Transform DeBut Advantages DeBut generalizes the square power of two butterfly factor matr

Sparse DETR By Byungseok Roh*, Jaewoong Shin*, Wuhyun Shin*, and Saehoon Kim at Kakao Brain. (*: Equal contribution) This repository is an official im

Semi-supervised Implicit Scene Completion from Sparse LiDAR Paper Created by Pengfei Li, Yongliang Shi, Tianyu Liu, Hao Zhao, Guyue Zhou and YA-QIN ZH

ESP32-IoT-button-graph-test ESP32 recording button presses, and serving webpage via webSockets in order to graph the responses. The objective was to t

GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Model This repository is the official PyTorch implementation of GraphRNN, a graph gene

Faster R-CNN pretrained on VisualGenome This repository modifies maskrcnn-benchmark for object detection and attribute prediction on VisualGenome data

Pyserini Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations. Retrieval using sparse re

Semi-supervised Implicit Scene Completion from Sparse LiDAR Paper Created by Pengfei Li, Yongliang Shi, Tianyu Liu, Hao Zhao, Guyue Zhou and YA-QIN ZH

SpConv: Spatially Sparse Convolution Library PyPI Install Downloads CPU (Linux Only) pip install spconv CUDA 10.2 pip install spconv-cu102 CUDA 11.1 p

Statistical tests for the sequential locality of graphs You can assess the statistical significance of the sequential locality of an adjacency matrix

Hidden-Fold Networks (HFN): Random Recurrent Residuals Using Sparse Supermasks by Ángel López García-Arias, Masanori Hashimoto, Masato Motomura, and J

Dynamic-Graphs-Construction Official Codes for Graph Modularity:Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Ne

📈 LipschitzLearningRates The code in this repository reproduces the experimental results on convergence rates for k-nearest neighbor graph infinity L

Accelerated Sparse Neural Training: A Provable and Efficient Method to FindN:M Transposable Masks Recently, researchers proposed pruning deep neural n

datastructures datastructures such as linked list, trees, graphs etc Made a public repository for coding enthusiasts. Those who want to collaborate on

PyNNDescent PyNNDescent is a Python nearest neighbor descent for approximate nearest neighbors. It provides a python implementation of Nearest Neighbo

Approximate Nearest Neighbor Search for Sparse Data in Python! This library is well suited to finding nearest neighbors in sparse, high dimensional spaces (like text documents).

Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).