3550 Repositories
Python deep-models Libraries
A PyTorch Implementation of "SINE: Scalable Incomplete Network Embedding" (ICDM 2018).
Scalable Incomplete Network Embedding ⠀⠀ A PyTorch implementation of Scalable Incomplete Network Embedding (ICDM 2018). Abstract Attributed network em
A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).
GAM ⠀⠀ A PyTorch implementation of Graph Classification Using Structural Attention (KDD 2018). Abstract Graph classification is a problem with practic
A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).
SimGNN ⠀⠀⠀ A PyTorch implementation of SimGNN: A Neural Network Approach to Fast Graph Similarity Computation (WSDM 2019). Abstract Graph similarity s
Implementation of character based convolutional neural network
Character Based CNN This repo contains a PyTorch implementation of a character-level convolutional neural network for text classification. The model a
A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).
APPNP ⠀ A PyTorch implementation of Predict then Propagate: Graph Neural Networks meet Personalized PageRank (ICLR 2019). Abstract Neural message pass
An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).
MixHop and N-GCN ⠀ A PyTorch implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019)
A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).
Splitter ⠀⠀ A PyTorch implementation of Splitter: Learning Node Representations that Capture Multiple Social Contexts (WWW 2019). Abstract Recent inte
A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).
CapsGNN ⠀⠀ A PyTorch implementation of Capsule Graph Neural Network (ICLR 2019). Abstract The high-quality node embeddings learned from the Graph Neur
The author's officially unofficial PyTorch BigGAN implementation.
BigGAN-PyTorch The author's officially unofficial PyTorch BigGAN implementation. This repo contains code for 4-8 GPU training of BigGANs from Large Sc
Implementation of experiments in the paper Clockwork Variational Autoencoders (project website) using JAX and Flax
Clockwork VAEs in JAX/Flax Implementation of experiments in the paper Clockwork Variational Autoencoders (project website) using JAX and Flax, ported
The Hailo Model Zoo includes pre-trained models and a full building and evaluation environment
Hailo Model Zoo The Hailo Model Zoo provides pre-trained models for high-performance deep learning applications. Using the Hailo Model Zoo you can mea
Official source for spanish Language Models and resources made @ BSC-TEMU within the "Plan de las Tecnologías del Lenguaje" (Plan-TL).
Spanish Language Models 💃🏻 Corpora 📃 Corpora Number of documents Size (GB) BNE 201,080,084 570GB Models 🤖 RoBERTa-base BNE: https://huggingface.co
A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)
SEAL ⠀⠀⠀ A PyTorch implementation of Semi-Supervised Graph Classification: A Hierarchical Graph Perspective (WWW 2019) Abstract Node classification an
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
ClusterGCN ⠀⠀ A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019). A
Implementation of QuickDraw - an online game developed by Google, combined with AirGesture - a simple gesture recognition application
QuickDraw - AirGesture Introduction Here is my python source code for QuickDraw - an online game developed by google, combined with AirGesture - a sim
🪄 Auto-generate Streamlit UI from Pydantic Models and Dataclasses.
Streamlit Pydantic Auto-generate Streamlit UI elements from Pydantic models. Getting Started • Documentation • Support • Report a Bug • Contribution •
Implementation of Invariant Point Attention, used for coordinate refinement in the structure module of Alphafold2, as a standalone Pytorch module
Invariant Point Attention - Pytorch Implementation of Invariant Point Attention as a standalone module, which was used in the structure module of Alph
Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data
LiDAR-MOS: Moving Object Segmentation in 3D LiDAR Data This repo contains the code for our paper: Moving Object Segmentation in 3D LiDAR Data: A Learn
Deep RGB-D Saliency Detection with Depth-Sensitive Attention and Automatic Multi-Modal Fusion (CVPR'2021, Oral)
DSA^2 F: Deep RGB-D Saliency Detection with Depth-Sensitive Attention and Automatic Multi-Modal Fusion (CVPR'2021, Oral) This repo is the official imp
Code for ViTAS_Vision Transformer Architecture Search
Vision Transformer Architecture Search This repository open source the code for ViTAS: Vision Transformer Architecture Search. ViTAS aims to search fo
Pytorch code for ICRA'21 paper: "Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation"
Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation This repository is the pytorch implementation of our paper: Hierarchical Cr
StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking
StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking Datasets You can download datasets that have been pre-pr
Computationally Efficient Optimization of Plackett-Luce Ranking Models for Relevance and Fairness
Computationally Efficient Optimization of Plackett-Luce Ranking Models for Relevance and Fairness This repository contains the code used for the exper
PyTorch implementation of paper: HPNet: Deep Primitive Segmentation Using Hybrid Representations.
HPNet This repository contains the PyTorch implementation of paper: HPNet: Deep Primitive Segmentation Using Hybrid Representations. Installation The
Official repository for the CVPR 2021 paper "Learning Feature Aggregation for Deep 3D Morphable Models"
Deep3DMM Official repository for the CVPR 2021 paper Learning Feature Aggregation for Deep 3D Morphable Models. Requirements This code is tested on Py
Parameterized Explainer for Graph Neural Network
PGExplainer This is a Tensorflow implementation of the paper: Parameterized Explainer for Graph Neural Network https://arxiv.org/abs/2011.04573 NeurIP
official implemntation for "Contrastive Learning with Stronger Augmentations"
CLSA CLSA is a self-supervised learning methods which focused on the pattern learning from strong augmentations. Copyright (C) 2020 Xiao Wang, Guo-Jun
Measuring and Improving Consistency in Pretrained Language Models
ParaRel 🤘 This repository contains the code and data for the paper: Measuring and Improving Consistency in Pretrained Language Models as well as the
Empirical Study of Transformers for Source Code & A Simple Approach for Handling Out-of-Vocabulary Identifiers in Deep Learning for Source Code
Transformers for variable misuse, function naming and code completion tasks The official PyTorch implementation of: Empirical Study of Transformers fo
source code for https://arxiv.org/abs/2005.11248 "Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics"
Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics This work will be published in Nature Biomedical
Unofficial Pytorch Implementation of WaveGrad2
WaveGrad 2 — Unofficial PyTorch Implementation WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis Unofficial PyTorch+Lightning Implementati
Self-supervised Deep LiDAR Odometry for Robotic Applications
DeLORA: Self-supervised Deep LiDAR Odometry for Robotic Applications Overview Paper: link Video: link ICRA Presentation: link This is the correspondin
Towards Debiasing NLU Models from Unknown Biases
Towards Debiasing NLU Models from Unknown Biases Abstract: NLU models often exploit biased features to achieve high dataset-specific performance witho
Automated machine learning: Review of the state-of-the-art and opportunities for healthcare
Automated machine learning: Review of the state-of-the-art and opportunities for healthcare
Implementation of Rotary Embeddings, from the Roformer paper, in Pytorch
Rotary Embeddings - Pytorch A standalone library for adding rotary embeddings to transformers in Pytorch, following its success as relative positional
The MLOps platform for innovators 🚀
DS2.ai is an integrated AI operation solution that supports all stages from custom AI development to deployment. It is an AI-specialized platform service that collects data, builds a training dataset through data labeling, and enables automatic development of artificial intelligence and easy deployment and operation.
A collection of research papers and software related to explainability in graph machine learning.
A collection of research papers and software related to explainability in graph machine learning.
A collection of 100 Deep Learning images and visualizations
A collection of Deep Learning images and visualizations. The project has been developed by the AI Summer team and currently contains almost 100 images.
A collection of 100 Deep Learning images and visualizations
A collection of Deep Learning images and visualizations. The project has been developed by the AI Summer team and currently contains almost 100 images.
Cancer metastasis detection with neural conditional random field (NCRF)
NCRF Prerequisites Data Whole slide images Annotations Patch images Model Training Testing Tissue mask Probability map Tumor localization FROC evaluat
A PyTorch implementation of " EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks."
EfficientNet A PyTorch implementation of EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. [arxiv] [Official TF Repo] Implemen
STEAL - Learning Semantic Boundaries from Noisy Annotations (CVPR 2019)
STEAL This is the official inference code for: Devil Is in the Edges: Learning Semantic Boundaries from Noisy Annotations David Acuna, Amlan Kar, Sanj
This repo contains the official implementations of EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis
EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis This repo contains the official implementations of EigenDamage: Structured Prunin
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening Introduction This is an implementation of the model used for breast
A PyTorch implementation of "DGC-Net: Dense Geometric Correspondence Network"
DGC-Net: Dense Geometric Correspondence Network This is a PyTorch implementation of our work "DGC-Net: Dense Geometric Correspondence Network" TL;DR A
A pytorch implementation of the ACL2019 paper "Simple and Effective Text Matching with Richer Alignment Features".
RE2 This is a pytorch implementation of the ACL 2019 paper "Simple and Effective Text Matching with Richer Alignment Features". The original Tensorflo
Pre-trained model, code, and materials from the paper "Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation" (MICCAI 2019).
Adaptive Segmentation Mask Attack This repository contains the implementation of the Adaptive Segmentation Mask Attack (ASMA), a targeted adversarial
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models Code accompanying CVPR'20 paper of the same title. Paper lin
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
This is a curated list of tutorials, projects, libraries, videos, papers, books and anything related to the incredible PyTorch. Feel free to make a pu
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
Generative Models Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow. Also present here are RBM and Helmholtz Machine. Note: Gen
Malmo Collaborative AI Challenge - Team Pig Catcher
The Malmo Collaborative AI Challenge - Team Pig Catcher Approach The challenge involves 2 agents who can either cooperate or defect. The optimal polic
deep learning model that learns to code with drawing in the Processing language
sketchnet sketchnet - processing code generator can we teach a computer to draw pictures with code. We use Processing and java/jruby code paired with
A community run, 5-day PyTorch Deep Learning Bootcamp
Deep Learning Winter School, November 2107. Tel Aviv Deep Learning Bootcamp : http://deep-ml.com. About Tel-Aviv Deep Learning Bootcamp is an intensiv
Amazon Forest Computer Vision: Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks
Amazon Forest Computer Vision Satellite Image tagging code using PyTorch / Keras Here is a sample of images we had to work with Source: https://www.ka
Torchreid: Deep learning person re-identification in PyTorch.
Torchreid Torchreid is a library for deep-learning person re-identification, written in PyTorch. It features: multi-GPU training support both image- a
PyTorch deep learning projects made easy.
PyTorch Template Project PyTorch deep learning project made easy. PyTorch Template Project Requirements Features Folder Structure Usage Config file fo
Kaggle | 9th place single model solution for TGS Salt Identification Challenge
UNet for segmenting salt deposits from seismic images with PyTorch. General We, tugstugi and xuyuan, have participated in the Kaggle competition TGS S
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
ocaml-torch provides some ocaml bindings for the PyTorch tensor library.
ocaml-torch provides some ocaml bindings for the PyTorch tensor library. This brings to OCaml NumPy-like tensor computations with GPU acceleration and tape-based automatic differentiation.
Serving PyTorch 1.0 Models as a Web Server in C++
Serving PyTorch Models in C++ This repository contains various examples to perform inference using PyTorch C++ API. Run git clone https://github.com/W
Rust bindings for the C++ api of PyTorch.
tch-rs Rust bindings for the C++ api of PyTorch. The goal of the tch crate is to provide some thin wrappers around the C++ PyTorch api (a.k.a. libtorc
🛠 All-in-one web-based IDE specialized for machine learning and data science.
All-in-one web-based development environment for machine learning Getting Started • Features & Screenshots • Support • Report a Bug • FAQ • Known Issu
An AI Assistant More Than a Toolkit
tymon An AI Assistant More Than a Toolkit The reason for creating framework tymon is simple. making AI more like an assistant, helping us to complete
Real-time multi-object tracker using YOLO v5 and deep sort
This repository contains a two-stage-tracker. The detections generated by YOLOv5, a family of object detection architectures and models pretrained on the COCO dataset, are passed to a Deep Sort algorithm which tracks the objects. It can track any object that your Yolov5 model was trained to detect.
RetinaFace: Deep Face Detection Library in TensorFlow for Python
RetinaFace is a deep learning based cutting-edge facial detector for Python coming with facial landmarks.
MONAI Label is a server-client system that facilitates interactive medical image annotation by using AI.
MONAI Label is a server-client system that facilitates interactive medical image annotation by using AI. It is an open-source and easy-to-install ecosystem that can run locally on a machine with one or two GPUs. Both server and client work on the same/different machine. However, initial support for multiple users is restricted. It shares the same principles with MONAI.
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.
This is the unofficial code of Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes. which achieve state-of-the-art trade-off between accuracy and speed on cityscapes and camvid, without using inference acceleration and extra data
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes Introduction This is the unofficial code of Deep Dual-re
Deep Learning and Logical Reasoning from Data and Knowledge
Logic Tensor Networks (LTN) Logic Tensor Network (LTN) is a neurosymbolic framework that supports querying, learning and reasoning with both rich data
NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling @ INTERSPEECH 2021 Accepted
NU-Wave — Official PyTorch Implementation NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling Junhyeok Lee, Seungu Han @ MINDsLab Inc
This repository contains the implementation of Deep Detail Enhancment for Any Garment proposed in Eurographics 2021
Deep-Detail-Enhancement-for-Any-Garment Introduction This repository contains the implementation of Deep Detail Enhancment for Any Garment proposed in
🤗 Push your spaCy pipelines to the Hugging Face Hub
spacy-huggingface-hub: Push your spaCy pipelines to the Hugging Face Hub This package provides a CLI command for uploading any trained spaCy pipeline
Fast sparse deep learning on CPUs
SPARSEDNN **If you want to use this repo, please send me an email: [email protected], or raise a Github issue. ** Fast sparse deep learning on CPUs
这个开源项目主要是对经典的时间序列预测算法论文进行复现,模型主要参考自GluonTS,框架主要参考自Informer
Time Series Research with Torch 这个开源项目主要是对经典的时间序列预测算法论文进行复现,模型主要参考自GluonTS,框架主要参考自Informer。 建立原因 相较于mxnet和TF,Torch框架中的神经网络层需要提前指定输入维度: # 建立线性层 TensorF
Project page for the paper Semi-Supervised Raw-to-Raw Mapping 2021.
Project page for the paper Semi-Supervised Raw-to-Raw Mapping 2021.
Recognize Handwritten Digits using Deep Learning on the browser itself.
MNIST on the Web An attempt to predict MNIST handwritten digits from my PyTorch model from the browser (client-side) and not from the server, with the
ML models implementation practice
Let's implement various ML algorithms with numpy/tf Vanilla Neural Network https://towardsdatascience.com/lets-code-a-neural-network-in-plain-numpy-ae
WAGMA-SGD is a decentralized asynchronous SGD for distributed deep learning training based on model averaging.
WAGMA-SGD is a decentralized asynchronous SGD based on wait-avoiding group model averaging. The synchronization is relaxed by making the collectives externally-triggerable, namely, a collective can be initiated without requiring that all the processes enter it. It partially reduces the data within non-overlapping groups of process, improving the parallel scalability.
Heimdall watchtower automatically sends you emails to notify you of the latest progress of your deep learning programs.
This software automatically sends you emails to notify you of the latest progress of your deep learning programs.
Denoising Diffusion Probabilistic Models
Denoising Diffusion Probabilistic Models This repo contains code for DDPM training. Based on Denoising Diffusion Probabilistic Models, Improved Denois
Spectral Tensor Train Parameterization of Deep Learning Layers
Spectral Tensor Train Parameterization of Deep Learning Layers This repository is the official implementation of our AISTATS 2021 paper titled "Spectr
Classify bird species based on their songs using SIamese Networks and 1D dilated convolutions.
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.
imbalanced-DL: Deep Imbalanced Learning in Python
imbalanced-DL: Deep Imbalanced Learning in Python Overview imbalanced-DL (imported as imbalanceddl) is a Python package designed to make deep imbalanc
This is my reading list for my PhD in AI, NLP, Deep Learning and more.
This is my reading list for my PhD in AI, NLP, Deep Learning and more.
TensorRT examples (Jetson, Python/C++)(object detection)
TensorRT examples (Jetson, Python/C++)(object detection)
Distributed DataLoader For Pytorch Based On Ray
Dpex——用户无感知分布式数据预处理组件 一、前言 随着GPU与CPU的算力差距越来越大以及模型训练时的预处理Pipeline变得越来越复杂,CPU部分的数据预处理已经逐渐成为了模型训练的瓶颈所在,这导致单机的GPU配置的提升并不能带来期望的线性加速。预处理性能瓶颈的本质在于每个GPU能够使用的C
Code for the paper "Implicit Representations of Meaning in Neural Language Models"
Implicit Representations of Meaning in Neural Language Models Preliminaries Create and set up a conda environment as follows: conda create -n state-pr
ElegantRL is featured with lightweight, efficient and stable, for researchers and practitioners.
Lightweight, efficient and stable implementations of deep reinforcement learning algorithms using PyTorch. 🔥
Global Filter Networks for Image Classification
Global Filter Networks for Image Classification Created by Yongming Rao, Wenliang Zhao, Zheng Zhu, Jiwen Lu, Jie Zhou This repository contains PyTorch
This package contains deep learning models and related scripts for RoseTTAFold
RoseTTAFold This package contains deep learning models and related scripts to run RoseTTAFold This repository is the official implementation of RoseTT
DFM: A Performance Baseline for Deep Feature Matching
DFM: A Performance Baseline for Deep Feature Matching Python (Pytorch) and Matlab (MatConvNet) implementations of our paper DFM: A Performance Baselin
An official TensorFlow implementation of “CLCC: Contrastive Learning for Color Constancy” accepted at CVPR 2021.
CLCC: Contrastive Learning for Color Constancy (CVPR 2021) Yi-Chen Lo*, Chia-Che Chang*, Hsuan-Chao Chiu, Yu-Hao Huang, Chia-Ping Chen, Yu-Lin Chang,
Implementation and replication of ProGen, Language Modeling for Protein Generation, in Jax
ProGen - (wip) Implementation and replication of ProGen, Language Modeling for Protein Generation, in Pytorch and Jax (the weights will be made easily
Official code of paper "PGT: A Progressive Method for Training Models on Long Videos" on CVPR2021
PGT Code for paper PGT: A Progressive Method for Training Models on Long Videos. Install Run pip install -r requirements.txt. Run python setup.py buil
Patch2Pix: Epipolar-Guided Pixel-Level Correspondences [CVPR2021]
Patch2Pix for Accurate Image Correspondence Estimation This repository contains the Pytorch implementation of our paper accepted at CVPR2021: Patch2Pi
Source code for models described in the paper "AudioCLIP: Extending CLIP to Image, Text and Audio" (https://arxiv.org/abs/2106.13043)
AudioCLIP Extending CLIP to Image, Text and Audio This repository contains implementation of the models described in the paper arXiv:2106.13043. This
This is the official repo for TransFill: Reference-guided Image Inpainting by Merging Multiple Color and Spatial Transformations at CVPR'21. According to some product reasons, we are not planning to release the training/testing codes and models. However, we will release the dataset and the scripts to prepare the dataset.
TransFill-Reference-Inpainting This is the official repo for TransFill: Reference-guided Image Inpainting by Merging Multiple Color and Spatial Transf
This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages" published in Findings of the Association for Computational Linguistics: ACL 2021.
XL-Sum This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Lang
PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing
PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing
Source code for paper: Knowledge Inheritance for Pre-trained Language Models
Knowledge-Inheritance Source code paper: Knowledge Inheritance for Pre-trained Language Models (preprint). The trained model parameters (in Fairseq fo