Python Graph-neural-networks Resources

Densely Connected Time Delay Neural Network PyTorch implementation of Densely Connected Time Delay Neural Network (D-TDNN) in our paper "Densely Conne

Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes Introduction This is the unofficial code of Deep Dual-re

NU-Wave — Official PyTorch Implementation NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling Junhyeok Lee, Seungu Han @ MINDsLab Inc

3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up Networks Introduction This repository contains the code and models for the follo

Neural Logic Inductive Learning This is the implementation of the Neural Logic Inductive Learning model (NLIL) proposed in the ICLR 2020 paper: Learn

Depth-supervised NeRF: Fewer Views and Faster Training for Free Project | Paper | YouTube Pytorch implementation of our method for learning neural rad

CLIPPER: A Graph-Theoretic Framework for Robust Data Association Data association is a fundamental problem in robotics and autonomy. CLIPPER provides

Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets This is the official PyTorch implementation for the paper Rapid Neural A

Self-supervised Graph-level Representation Learning with Local and Global Structure Introduction This project is an implementation of ``Self-supervise

Heterogeneous INteract and aggreGatE (GraphHINGE) This is a pytorch implementation of GraphHINGE model. This is the experiment code in the following w

**Codebase and data are uploaded in progress. ** VOLT(-py) is a vocabulary learning codebase that allows researchers and developers to automaticaly ge

Box is a text-based visual programming language inspired by Unreal Engine blueprint function graphs. $ cat factorial.box ┌─ƒ(Factorial)───┐

alias-free-gan-pytorch Unofficial implementation of Alias-Free Generative Adversarial Networks. (https://arxiv.org/abs/2106.12423) This implementation

Easy-To-Hard The official repository for the paper "Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks". Gett

Official PyTorch implementation of the preprint paper "Stylized Neural Painting", accepted to CVPR 2021.

Integrating Amazon API Gateway private endpoints with on-premises networks Read the blog about this application: Integrating Amazon API Gateway privat

The goal is to classify different birds species based on their songs/calls. Spectrograms have been extracted from the audio samples and used as features for classification.

GCResNet PyTorch implementation of Graph Convolutional Networks in Feature Space for Image Deblurring and Super-resolution, IJCNN 2021. The code will

This is my reading list for my PhD in AI, NLP, Deep Learning and more.

GPRGNN This is the source code for our ICLR2021 paper: Adaptive Universal Generalized PageRank Graph Neural Network. Hidden state feature extraction i

Physics-aware Difference Graph Networks for Sparsely-Observed Dynamics This repository is the official PyTorch implementation of "Physics-aware Differ

Balancing Training for Multilingual Neural Machine Translation Implementation of the paper Balancing Training for Multilingual Neural Machine Translat

REval Table of Contents Introduction Overview Requirements Installation Probing Usage Citation License 🎓 Introduction REval is a simple framework for

Implicit Representations of Meaning in Neural Language Models Preliminaries Create and set up a conda environment as follows: conda create -n state-pr

Global Filter Networks for Image Classification Created by Yongming Rao, Wenliang Zhao, Zheng Zhu, Jiwen Lu, Jie Zhou This repository contains PyTorch

gym-anm is a framework for designing reinforcement learning (RL) environments that model Active Network Management (ANM) tasks in electricity distribution networks. It is built on top of the OpenAI Gym toolkit.

Learning Canonical Representations for Scene Graph to Image Generation (ECCV 2020) Roei Herzig*, Amir Bar*, Huijuan Xu, Gal Chechik, Trevor Darrell, A

R-Drop: Regularized Dropout for Neural Networks R-drop is a simple yet very effective regularization method built upon dropout, by minimizing the bidi

MTTS-CAN: Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement Paper Xin Liu, Josh Fromm, Shwetak Patel, Daniel M

FastPitchFormant - PyTorch Implementation PyTorch Implementation of FastPitchFormant: Source-filter based Decomposed Modeling for Speech Synthesis. Qu

AnalyticMesh Analytic Marching is an exact meshing solution from neural networks. Compared to standard methods, it completely avoids geometric and top

Graph-to-Graph Transformers Self-attention models, such as Transformer, have been hugely successful in a wide range of natural language processing (NL

Recurrent Fast Weight Programmers This is the official repository containing the code we used to produce the experimental results reported in the pape

PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing

Graph4NLP Graph4NLP is an easy-to-use library for R&D at the intersection of Deep Learning on Graphs and Natural Language Processing (i.e., DLG4NLP).

Graph Transformer - Pytorch Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2. This was recently used by bot

A ready-to-use framework of latest models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, and etc.

Non-autoregressive Deep Learning-Based TTS Template This is a template for the Non-autoregressive TTS model. It contains Data Preprocessing Pipeline D

EdMIPS is an efficient algorithm to search the optimal mixed-precision neural network directly without proxy task on ImageNet given computation budgets. It can be applied to many popular network architectures, including ResNet, GoogLeNet, and Inception-V3.

DeepCDR Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network This work has been accepted to ECCB2020 and was also published in the

SNN_Calibration Pytorch Implementation of Spiking Neural Networks Calibration, ICML 2021 Feature Comparison of SNN calibration: Features SNN Direct Tr

AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis | Project Page | Paper | PyTorch implementation for the paper "AD-NeRF: Audio

Soft DTW Loss Function for PyTorch in CUDA This is a Pytorch Implementation of Soft-DTW: a Differentiable Loss Function for Time-Series which is batch

PyTorch code to reproduce LyDROO algorithm [1], which is an online computation offloading algorithm to maximize the network data processing capability subject to the long-term data queue stability and average power constraints. It applies Lyapunov optimization to decouple the multi-stage stochastic MINLP into deterministic per-frame MINLP subproblems and solves each subproblem via DROO algorithm. It includes:

The inductive bias of a neural network is largely determined by the architecture and the training algorithm. To achieve good generalization, how to effectively train a neural network is of great importance. We propose a novel orthogonal over-parameterized training (OPT) framework that can provably minimize the hyperspherical energy which characterizes the diversity of neurons on a hypersphere. See our previous work -- MHE for an in-depth introduction.

DeepProbLog DeepProbLog is an extension of ProbLog that integrates Probabilistic Logic Programming with deep learning by introducing the neural predic

Neural G2P to portuguese language Grapheme-to-phoneme (G2P) conversion is the process of generating pronunciation for words based on their written for

WaveGrad2 - PyTorch Implementation PyTorch Implementation of Google Brain's WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis. Status (202

π-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis Project Page | Paper | Data Eric Ryan Chan*, Marco Monteiro*, Pe

Image Translation with ASAPNets Spatially-Adaptive Pixelwise Networks for Fast Image Translation, CVPR 2021 Webpage | Paper | Video Installation insta

FinGAT: A Financial Graph Attention Networkto Recommend Top-K Profitable Stocks This is our implementation for the paper: FinGAT: A Financial Graph At

This repository is the official PyTorch implementation of Meta-Balance. Find the paper on arxiv MetaBalance: High-Performance Neural Networks for Clas

Learning Neural Network Subspaces Welcome to the codebase for Learning Neural Network Subspaces by Mitchell Wortsman, Maxwell Horton, Carlos Guestrin,

Decoupled Dynamic Filter Networks This repo is the official implementation of CVPR2021 paper: "Decoupled Dynamic Filter Networks". Introduction DDF is

Random Walk Graph Neural Networks This repository is the official implementation of Random Walk Graph Neural Networks. Requirements Code is written in

Temporal Query Networks for Fine-grained Video Understanding 📋 This repository contains the implementation of CVPR2021 paper Temporal_Query_Networks

JittorVis - Visual understanding of deep learning model.

The `rtdl` library + The official implementation of the paper "Revisiting Deep Learning Models for Tabular Data"

AWS_ORG_MAPPER This tool uses sso-oidc to authenticate to the AWS organization. Once authenticated the tool will attempt to enumerate all users and ro

ContextNet ContextNet has CNN-RNN-transducer architecture and features a fully convolutional encoder that incorporates global context information into

We present Graph Neural Diffusion (GRAND) that approaches deep learning on graphs as a continuous diffusion process and treats Graph Neural Networks (GNNs) as discretisations of an underlying PDE.

The final code for OGB Installation Requirements: ogb=1.3.1 torch=1.7.0 torch-geometric=1.7.0 torch-scatter=2.0.6 torch-sparse=0.6.9 Baseline models T

Cloud-native neural search framework for any kind of data

AnimeGAN - Deep Convolutional Generative Adverserial Network PyTorch implementation of DCGAN introduced in the paper: Unsupervised Representation Lear

End to End Automatic Speech Recognition In this repository, I have developed an end to end Automatic speech recognition project. I have developed the

Segmentation and Identification of Vertebrae in CT Scans using CNN, k-means Clustering and k-NN If you use this code for your research, please cite ou

Neural Surface Maps Official implementation of Neural Surface Maps - Luca Morreale, Noam Aigerman, Vladimir Kim, Niloy J. Mitra [Paper] [Project Page]

nam-pytorch Unofficial PyTorch implementation of Neural Additive Models (NAM) by Agarwal, et al. [abs, pdf] Installation You can access nam-pytorch vi

SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networks (CVPR 2021 Oral) This repository contains the official PyTorch implementation

Neural Deformation Graphs Project Page | Paper | Video Neural Deformation Graphs for Globally-consistent Non-rigid Reconstruction Aljaž Božič, Pablo P

Spiking Neural Network training with EventProp This is an unofficial PyTorch implemenation of EventProp, a method to compute exact gradients for Spiki

LMs for biomedical KG completion This repository contains code to run the experiments described in: Scientific Language Models for Biomedical Knowledg

NBEATSx: Neural basis expansion analysis with exogenous variables We extend the NBEATS model to incorporate exogenous factors. The resulting method, c

Graph Contrastive Learning Automated PyTorch implementation for Graph Contrastive Learning Automated [talk] [poster] [appendix] Yuning You, Tianlong C

Deep Networks from the Principle of Rate Reduction This repository is the official NumPy implementation of the paper Deep Networks from the Principle

NAS-Bench-Macro This repository includes the benchmark and code for NAS-Bench-Macro in paper "Prioritized Architecture Sampling with Monto-Carlo Tree

This is the repo for the paper: Leveraging Two Types of Global Graph for Sequential Fashion Recommendation Requirements OS: Ubuntu 16.04 or higher ver

Habitat: A Runtime-Based Computational Performance Predictor for Deep Neural Network Training Habitat is a tool that predicts a deep neural network's

UnivNet UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation. Training python train.py --c

In the light of feature distributions: Moment matching for Neural Style Transfer (CVPR 2021) This repository provides code to recreate results present

XVFI This is the official repository of XVFI (eXtreme Video Frame Interpolation), https://arxiv.org/abs/2103.16206 Last Update: 20210607 We provide th

What is being transferred in transfer learning? This repo contains the code for the following paper: Behnam Neyshabur*, Hanie Sedghi*, Chiyuan Zhang*.

Welcome to Barlow Barlow is a tool for identifying the failure modes for a given neural network. To achieve this, Barlow first creates a group of imag

Styleformer A Neural Language Style Transfer framework to transfer natural language text smoothly between fine-grained language styles like formal/cas

Deep Reinforcement Learning Library built on top of Neural Network Libraries NNablaRL is a deep reinforcement learning library built on top of Neural

YANMTT YANMTT is short for Yet Another Neural Machine Translation Toolkit. For a backstory how I ended up creating this toolkit scroll to the bottom o

Orientation independent Möbius CNNs This repository implements and evaluates convolutional networks on the Möbius strip as toy model instantiations of

Graphormer By Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng*, Guolin Ke, Di He*, Yanming Shen and Tie-Yan Liu. This repo is the official impl

EPSANet：An Efficient Pyramid Split Attention Block on Convolutional Neural Network This repo contains the official Pytorch implementaion code and conf

StyleSpeech - PyTorch Implementation PyTorch Implementation of Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation. Status (2021.06.13

Point 4D Transformer Networks for Spatio-Temporal Modeling in Point Cloud Videos Introduction Point cloud videos exhibit irregularities and lack of or

Neural Ensemble Search Introduction This repo contains the code accompanying the paper: Neural Ensemble Search for Performant and Calibrated Predictio

Deep Deterministic Uncertainty This repository contains the code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic

PyGAS: Auto-Scaling GNNs in PyG PyGAS is the practical realization of our G NN A uto S cale (GAS) framework, which scales arbitrary message-passing GN

HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis Jungil Kong, Jaehyeon Kim, Jaekyoung Bae In our paper, we p

Graph-to-Tree Learning for Solving Math Word Problems PyTorch implementation of Graph based Math Word Problem solver described in our ACL 2020 paper G

Segformer - Pytorch Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch. Install $ pip install segformer-pytorch

STCN Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang [a

merlot MERLOT: Multimodal Neural Script Knowledge Models MERLOT is a model for learning what we are calling "neural script knowledge" -- representatio

This repository is the official PyTorch implementation of SAINT. Find the paper on arxiv SAINT: Improved Neural Networks for Tabular Data via Row Atte