1974 Repositories
Python resilient-swarm-communications-with-meta-graph-convolutional-networks Libraries
VACA: Designing Variational Graph Autoencoders for Interventional and Counterfactual Queries
VACA Code repository for the paper "VACA: Designing Variational Graph Autoencoders for Interventional and Counterfactual Queries (arXiv)". The impleme
Rot-Pro: Modeling Transitivity by Projection in Knowledge Graph Embedding
Rot-Pro : Modeling Transitivity by Projection in Knowledge Graph Embedding This repository contains the source code for the Rot-Pro model, presented a
Meta-Learning Sparse Implicit Neural Representations (NeurIPS 2021)
Meta-SparseINR Official PyTorch implementation of "Meta-learning Sparse Implicit Neural Representations" (NeurIPS 2021) by Jaeho Lee*, Jihoon Tack*, N
Node Dependent Local Smoothing for Scalable Graph Learning
Node Dependent Local Smoothing for Scalable Graph Learning Requirements Environments: Xeon Gold 5120 (CPU), 384GB(RAM), TITAN RTX (GPU), Ubuntu 16.04
This repo is the official implementation of "L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization".
L2ight is a closed-loop ONN on-chip learning framework to enable scalable ONN mapping and efficient in-situ learning. L2ight adopts a three-stage learning flow that first calibrates the complicated photonic circuit states under challenging physical constraints, then performs photonic core mapping via combined analytical solving and zeroth-order optimization.
TCPNet - Temporal-attentive-Covariance-Pooling-Networks-for-Video-Recognition
Temporal-attentive-Covariance-Pooling-Networks-for-Video-Recognition This is an implementation of TCPNet. Introduction For video recognition task, a g
Learning where to learn - Gradient sparsity in meta and continual learning
Learning where to learn - Gradient sparsity in meta and continual learning In this paper, we investigate gradient sparsity found by MAML in various co
Code for approximate graph reduction techniques for cardinality-based DSFM, from paper
SparseCard Code for approximate graph reduction techniques for cardinality-based DSFM, from paper "Approximate Decomposable Submodular Function Minimi
Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks
Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks Setup This implementation is based on PyTorch = 1.0.0. Smal
SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs
SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs SMORE is a a versatile framework that scales multi-hop query emb
SimplEx - Explaining Latent Representations with a Corpus of Examples
SimplEx - Explaining Latent Representations with a Corpus of Examples Code Author: Jonathan Crabbé ([email protected]) This repository contains the imp
OneFlow is a performance-centered and open-source deep learning framework.
OneFlow OneFlow is a performance-centered and open-source deep learning framework. Latest News Version 0.5.0 is out! First class support for eager exe
Hierarchical User Intent Graph Network for Multimedia Recommendation
Hierarchical User Intent Graph Network for Multimedia Recommendation This is our Pytorch implementation for the paper: Hierarchical User Intent Graph
Resilient Adaptive Parallel sImulator for griD (rapid)
Rapid is an open-source software library that implements a novel “parallel-in-time” (Parareal) algorithm and semi-analytical solutions for co-simulation of integrated transmission and distribution systems.
Recognize numbers from an (28 x 28) image using neural networks
Number recognition Recognize numbers from a 28 x 28 image using neural networks Usage This is an example of a simple usage of number-recognition NOTE:
With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function
With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function. At the moment, only TensorFlow sequential models are supported. Interfaces to either the Pyomo or Gurobi modeling environments are offered.
Video Matting via Consistency-Regularized Graph Neural Networks
Video Matting via Consistency-Regularized Graph Neural Networks Project Page | Real Data | Paper Installation Our code has been tested on Python 3.7,
Covid-19 Test AI (Deep Learning - NNs) Software. Accuracy is the %96.5, loss is the 0.09 :)
Covid-19 Test AI (Deep Learning - NNs) Software I developed a segmentation algorithm to understand whether Covid-19 Test Photos are positive or negati
Predicting lncRNA–protein interactions based on graph autoencoders and collaborative training
Predicting lncRNA–protein interactions based on graph autoencoders and collaborative training Code for our paper "Predicting lncRNA–protein interactio
Pytorch implementation of Cut-Thumbnail in the paper Cut-Thumbnail:A Novel Data Augmentation for Convolutional Neural Network.
Cut-Thumbnail (Accepted at ACM MULTIMEDIA 2021) Tianshu Xie, Xuan Cheng, Xiaomin Wang, Minghui Liu, Jiali Deng, Tao Zhou, Ming Liu This is the officia
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees This repository is the official implementation of the empirica
Space Time Recurrent Memory Network - Pytorch
Space Time Recurrent Memory Network - Pytorch (wip) Implementation of Space Time Recurrent Memory Network, recurrent network competitive with attentio
Sharing of contents on mitochondrial encounter networks
mito-network-sharing Sharing of contents on mitochondrial encounter networks Required: R with igraph, brainGraph, ggplot2, and XML libraries; igraph l
Code of the paper "Multi-Task Meta-Learning Modification with Stochastic Approximation".
Multi-Task Meta-Learning Modification with Stochastic Approximation This repository contains the code for the paper "Multi-Task Meta-Learning Modifica
Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance
Nested Graph Neural Networks About Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance.
Exponential Graph is Provably Efficient for Decentralized Deep Training
Exponential Graph is Provably Efficient for Decentralized Deep Training This code repository is for the paper Exponential Graph is Provably Efficient
The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information".
The HIST framework for stock trend forecasting The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining C
This is an official PyTorch implementation of Task-Adaptive Neural Network Search with Meta-Contrastive Learning (NeurIPS 2021, Spotlight).
NeurIPS 2021 (Spotlight): Task-Adaptive Neural Network Search with Meta-Contrastive Learning This is an official PyTorch implementation of Task-Adapti
The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information".
The HIST framework for stock trend forecasting The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining C
The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021
Directed Graph Contrastive Learning The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL). In this paper, we present the first con
TrackTech: Real-time tracking of subjects and objects on multiple cameras
TrackTech: Real-time tracking of subjects and objects on multiple cameras This project is part of the 2021 spring bachelor final project of the Bachel
Simple PyTorch hierarchical models.
A python package adding basic hierarchal networks in pytorch for classification tasks. It implements a simple hierarchal network structure based on feed-backward outputs.
A Nim frontend for pytorch, aiming to be mostly auto-generated and internally using ATen.
Master Release Pytorch - Py + Nim A Nim frontend for pytorch, aiming to be mostly auto-generated and internally using ATen. Because Nim compiles to C+
A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN)
A PyTorch Implementation of GGNN This is a PyTorch implementation of the Gated Graph Sequence Neural Networks (GGNN) as described in the paper Gated G
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
Graph ConvNets in PyTorch October 15, 2017 Xavier Bresson http://www.ntu.edu.sg/home/xbresson https://github.com/xbresson https://twitter.com/xbresson
Multi-layer convolutional LSTM with Pytorch
Convolution_LSTM_pytorch Thanks for your attention. I haven't got time to maintain this repo for a long time. I recommend this repo which provides an
Count the frequency of letters or words in a text file and show a graph.
Word Counter By EBUS Coding Club Count the frequency of letters or words in a text file and show a graph. Requirements Python 3.9 or higher matplotlib
Official PyTorch(Geometric) implementation of DPGNN(DPGCN) in "Distance-wise Prototypical Graph Neural Network for Node Imbalance Classification"
DPGNN This repository is an official PyTorch(Geometric) implementation of DPGNN(DPGCN) in "Distance-wise Prototypical Graph Neural Network for Node Im
Dynamic Graph Event Detection
DyGED Dynamic Graph Event Detection Get Started pip install -r requirements.txt TODO Paper link to arxiv, and how to cite. Twitter Weather dataset tra
EgoNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale
EgonNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale Paper: EgoNN: Egocentric Neural Network for Point Cloud
Harmonic Memory Networks for Graph Completion
HMemNetworks Code and documentation for Harmonic Memory Networks, a series of models for compositionally assembling representations of graph elements
A Broader Picture of Random-walk Based Graph Embedding
Random-walk Embedding Framework This repository is a reference implementation of the random-walk embedding framework as described in the paper: A Broa
CvT-ASSD: Convolutional vision-Transformerbased Attentive Single Shot MultiBox Detector (ICTAI 2021 CCF-C 会议)The 33rd IEEE International Conference on Tools with Artificial Intelligence
CvT-ASSD including extra CvT, CvT-SSD, VGG-ASSD models original-code-website: https://github.com/albert-jin/CvT-SSD new-code-website: https://github.c
A Context-aware Visual Attention-based training pipeline for Object Detection from a Webpage screenshot!
CoVA: Context-aware Visual Attention for Webpage Information Extraction Abstract Webpage information extraction (WIE) is an important step to create k
DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks
DECAF (DEbiasing CAusal Fairness) Code Author: Trent Kyono This repository contains the code used for the "DECAF: Generating Fair Synthetic Data Using
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks This is the master thesi
A novel pipeline framework for multi-hop complex KGQA task. About the paper title: Improving Multi-hop Embedded Knowledge Graph Question Answering by Introducing Relational Chain Reasoning
Rce-KGQA A novel pipeline framework for multi-hop complex KGQA task. This framework mainly contains two modules, answering_filtering_module and relati
Wanli Li and Tieyun Qian: Exploit a Multi-head Reference Graph for Semi-supervised Relation Extraction, IJCNN 2021
MRefG Wanli Li and Tieyun Qian: "Exploit a Multi-head Reference Graph for Semi-supervised Relation Extraction", IJCNN 2021 1. Requirements To reproduc
CBREN: Convolutional Neural Networks for Constant Bit Rate Video Quality Enhancement
CBREN This is the Pytorch implementation for our IEEE TCSVT paper : CBREN: Convolutional Neural Networks for Constant Bit Rate Video Quality Enhanceme
This repository is the code of the paper "Sparse Spatial Transformers for Few-Shot Learning".
🌟 Sparse Spatial Transformers for Few-Shot Learning This code implements the Sparse Spatial Transformers for Few-Shot Learning(SSFormers). Our code i
Polynomial-time Meta-Interpretive Learning
Louise - polynomial-time Program Learning Getting help with Louise Louise's author can be reached by email at [email protected]. Please use this email t
PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Condition Layer Normalization and Semi-Supervised Training in Text-To-Speech
Cross-Speaker-Emotion-Transfer - PyTorch Implementation PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Conditio
Attentive Implicit Representation Networks (AIR-Nets)
Attentive Implicit Representation Networks (AIR-Nets) Preprint | Supplementary | Accepted at the International Conference on 3D Vision (3DV) teaser.mo
This code uses generative adversarial networks to generate diverse task allocation plans for Multi-agent teams.
Mutli-agent task allocation This code uses generative adversarial networks to generate diverse task allocation plans for Multi-agent teams. To change
Convolutional neural network web app trained to track our infant’s sleep schedule using our Google Nest camera.
Machine Learning Sleep Schedule Tracker What is it? Convolutional neural network web app trained to track our infant’s sleep schedule using our Google
Neo4j Movies Example application with Flask backend using the neo4j-python-driver
Neo4j Movies Application: Quick Start This example application demonstrates how easy it is to get started with Neo4j in Python. It is a very simple we
Deep Networks with Recurrent Layer Aggregation
RLA-Net: Recurrent Layer Aggregation Recurrence along Depth: Deep Networks with Recurrent Layer Aggregation This is an implementation of RLA-Net (acce
Attentive Implicit Representation Networks (AIR-Nets)
Attentive Implicit Representation Networks (AIR-Nets) Preprint | Supplementary | Accepted at the International Conference on 3D Vision (3DV) teaser.mo
This is the code of "Multi-view Contrastive Graph Clustering" in NeurlPS 2021.
MCGC Description This is the code of "Multi-view Contrastive Graph Clustering" in NeurlPS 2021. Datasets Results ACM DBLP IMDB Amazon photos Amazon co
Segmentation models with pretrained backbones. PyTorch.
Python library with Neural Networks for Image Segmentation based on PyTorch. The main features of this library are: High level API (just two lines to
This code provides various models combining dilated convolutions with residual networks
Overview This code provides various models combining dilated convolutions with residual networks. Our models can achieve better performance with less
PyTorch implementation of Convolutional Neural Fabrics http://arxiv.org/abs/1606.02492
PyTorch implementation of Convolutional Neural Fabrics arxiv:1606.02492 There are some minor differences: The raw image is first convolved, to obtain
Very Deep Convolutional Networks for Large-Scale Image Recognition
pytorch-vgg Some scripts to convert the VGG-16 and VGG-19 models [1] from Caffe to PyTorch. The converted models can be used with the PyTorch model zo
Convolutional Recurrent Neural Network (CRNN) for image-based sequence recognition.
Convolutional Recurrent Neural Network This software implements the Convolutional Recurrent Neural Network (CRNN), a combination of CNN, RNN and CTC l
Training Very Deep Neural Networks Without Skip-Connections
DiracNets v2 update (January 2018): The code was updated for DiracNets-v2 in which we removed NCReLU by adding per-channel a and b multipliers without
PyTorch code for the "Deep Neural Networks with Box Convolutions" paper
Box Convolution Layer for ConvNets Single-box-conv network (from `examples/mnist.py`) learns patterns on MNIST What This Is This is a PyTorch implemen
PyTorch implementation of Octave Convolution with pre-trained Oct-ResNet and Oct-MobileNet models
octconv.pytorch PyTorch implementation of Octave Convolution in Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octa
Convolutional Neural Network for 3D meshes in PyTorch
MeshCNN in PyTorch SIGGRAPH 2019 [Paper] [Project Page] MeshCNN is a general-purpose deep neural network for 3D triangular meshes, which can be used f
A Pytorch implementation of "LegoNet: Efficient Convolutional Neural Networks with Lego Filters" (ICML 2019).
LegoNet This code is the implementation of ICML2019 paper LegoNet: Efficient Convolutional Neural Networks with Lego Filters Run python train.py You c
Django database backed celery periodic task scheduler with support for task dependency graph
Djag Scheduler (Dj)ango Task D(AG) (Scheduler) Overview Djag scheduler associates scheduling information with celery tasks The task schedule is persis
Spatial-Temporal Transformer for Dynamic Scene Graph Generation, ICCV2021
Spatial-Temporal Transformer for Dynamic Scene Graph Generation Pytorch Implementation of our paper Spatial-Temporal Transformer for Dynamic Scene Gra
Warren - Stock Price Predictor
Web app to predict closing stock prices in real time using Facebook's Prophet time series algorithm with a multi-variate, single-step time series forecasting strategy.
Code for "Generative adversarial networks for reconstructing natural images from brain activity".
Reconstruct handwritten characters from brains using GANs Example code for the paper "Generative adversarial networks for reconstructing natural image
Self-supervised learning on Graph Representation Learning (node-level task)
graph_SSL Self-supervised learning on Graph Representation Learning (node-level task) How to run the code To run GRACE, sh run_GRACE.sh To run GCA, sh
[TPAMI 2021] iOD: Incremental Object Detection via Meta-Learning
Incremental Object Detection via Meta-Learning To appear in an upcoming issue of the IEEE Transactions on Pattern Analysis and Machine Intelligence (T
The official implementation of paper Siamese Transformer Pyramid Networks for Real-Time UAV Tracking, accepted by WACV22
SiamTPN Introduction This is the official implementation of the SiamTPN (WACV2022). The tracker intergrates pyramid feature network and transformer in
Key information extraction from invoice document with Graph Convolution Network
Key Information Extraction from Scanned Invoices Key information extraction from invoice document with Graph Convolution Network Related blog post fro
This is the code of NeurIPS'21 paper "Towards Enabling Meta-Learning from Target Models".
ST This is the code of NeurIPS 2021 paper "Towards Enabling Meta-Learning from Target Models". If you use any content of this repo for your work, plea
CVNets: A library for training computer vision networks
CVNets: A library for training computer vision networks This repository contains the source code for training computer vision models. Specifically, it
CoSMA: Convolutional Semi-Regular Mesh Autoencoder. From Paper "Mesh Convolutional Autoencoder for Semi-Regular Meshes of Different Sizes"
Mesh Convolutional Autoencoder for Semi-Regular Meshes of Different Sizes Implementation of CoSMA: Convolutional Semi-Regular Mesh Autoencoder arXiv p
[NeurIPS2021] Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Code for NeurIPS 2021 Paper "Exploring Architectural Ingredients of A
Meta graph convolutional neural network-assisted resilient swarm communications
Resilient UAV Swarm Communications with Graph Convolutional Neural Network This repository contains the source codes of Resilient UAV Swarm Communicat
For auto aligning, cropping, and scaling HR and LR images for training image based neural networks
ImgAlign For auto aligning, cropping, and scaling HR and LR images for training image based neural networks Usage Make sure OpenCV is installed, 'pip
Implements Stacked-RNN in numpy and torch with manual forward and backward functions
Recurrent Neural Networks Implements simple recurrent network and a stacked recurrent network in numpy and torch respectively. Both flavours implement
Understanding Convolutional Neural Networks from Theoretical Perspective via Volterra Convolution
nnvolterra Run Code Compile first: make compile Run all codes: make all Test xconv: make npxconv_test MNIST dataset needs to be downloaded, converted
Code for reproducing our paper: LMSOC: An Approach for Socially Sensitive Pretraining
LMSOC: An Approach for Socially Sensitive Pretraining Code for reproducing the paper LMSOC: An Approach for Socially Sensitive Pretraining to appear a
BMVC 2021: This is the github repository for "Few Shot Temporal Action Localization using Query Adaptive Transformers" accepted in British Machine Vision Conference (BMVC) 2021, Virtual
FS-QAT: Few Shot Temporal Action Localization using Query Adaptive Transformer Accepted as Poster in BMVC 2021 This is an official implementation in P
CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP
CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP Andreas Fürst* 1, Elisabeth Rumetshofer* 1, Viet Tran1, Hubert Ramsauer1, Fei Tang3, Joh
Bayesian Meta-Learning Through Variational Gaussian Processes
vmgp This is the repository of Vivek Myers and Nikhil Sardana for our CS 330 final project, Bayesian Meta-Learning Through Variational Gaussian Proces
MEND: Model Editing Networks using Gradient Decomposition
MEND: Model Editing Networks using Gradient Decomposition Setup Environment This codebase uses Python 3.7.9. Other versions may work as well. Create a
Official implementation of CVPR2020 paper "Deep Generative Model for Robust Imbalance Classification"
Deep Generative Model for Robust Imbalance Classification Deep Generative Model for Robust Imbalance Classification Xinyue Wang, Yilin Lyu, Liping Jin
Website which uses Deep Learning to generate horror stories.
Creepypasta - Text Generator Website which uses Deep Learning to generate horror stories. View Demo · View Website Repo · Report Bug · Request Feature
The end-to-end platform for building voice products at scale
Picovoice Made in Vancouver, Canada by Picovoice Picovoice is the end-to-end platform for building voice products on your terms. Unlike Alexa and Goog
A MNIST-like fashion product database. Benchmark
Fashion-MNIST Table of Contents Why we made Fashion-MNIST Get the Data Usage Benchmark Visualization Contributing Contact Citing Fashion-MNIST License
A plug-and-play library for neural networks written in Python
A plug-and-play library for neural networks written in Python!
Simple CLI python app to show a stocks graph performance. Made with Matplotlib and Tiingo.
stock-graph-python Simple CLI python app to show a stocks graph performance. Made with Matplotlib and Tiingo. Tiingo API Key You will need to add your
Deep learning library for solving differential equations and more
DeepXDE Voting on whether we should have a Slack channel for discussion. DeepXDE is a library for scientific machine learning. Use DeepXDE if you need
A Real-Time-Strategy game for Deep Learning research
Description DeepRTS is a high-performance Real-TIme strategy game for Reinforcement Learning research. It is written in C++ for performance, but provi
Retentioneering: product analytics, data-driven customer journey map optimization, marketing analytics, web analytics, transaction analytics, graph visualization, and behavioral segmentation with customer segments in Python.
What is Retentioneering? Retentioneering is a Python framework and library to assist product analysts and marketing analysts as it makes it easier to
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa