2838 Repositories
Python neural-topic-models Libraries
High performance distributed framework for training deep learning recommendation models based on PyTorch.
PERSIA (Parallel rEcommendation tRaining System with hybrId Acceleration) is developed by AI platform@Kuaishou Technology, collaborating with ETH. It
Conversational text Analysis using various NLP techniques
PyConverse Let me try first Installation pip install pyconverse Usage Please try this notebook that demos the core functionalities: basic usage noteb
Use tensorflow to implement a Deep Neural Network for real time lane detection
LaneNet-Lane-Detection Use tensorflow to implement a Deep Neural Network for real time lane detection mainly based on the IEEE IV conference paper "To
Implementation of ICCV19 Paper "Learning Two-View Correspondences and Geometry Using Order-Aware Network"
OANet implementation Pytorch implementation of OANet for ICCV'19 paper "Learning Two-View Correspondences and Geometry Using Order-Aware Network", by
The FIRST GANs-based omics-to-omics translation framework
OmiTrans Please also have a look at our multi-omics multi-task DL freamwork đź‘€ : OmiEmbed The FIRST GANs-based omics-to-omics translation framework Xi
Package to compute Mauve, a similarity score between neural text and human text. Install with `pip install mauve-text`.
MAUVE MAUVE is a library built on PyTorch and HuggingFace Transformers to measure the gap between neural text and human text with the eponymous MAUVE
Make differentially private training of transformers easy for everyone
private-transformers This codebase facilitates fast experimentation of differentially private training of Hugging Face transformers. What is this? Why
Learning Convolutional Neural Networks with Interactive Visualization.
CNN Explainer An interactive visualization system designed to help non-experts learn about Convolutional Neural Networks (CNNs) For more information,
Pytorch library for end-to-end transformer models training and serving
Pytorch library for end-to-end transformer models training and serving
labelpix is a graphical image labeling interface for drawing bounding boxes
Welcome to labelpix 👋 labelpix is a graphical image labeling interface for drawing bounding boxes. 🏠Homepage Install pip install -r requirements.tx
This program will stylize your photos with fast neural style transfer.
Neural Style Transfer (NST) Using TensorFlow Demo TensorFlow TensorFlow is an end-to-end open source platform for machine learning. It has a comprehen
DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation
DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation This repository is the implementation of DynaTune paper. This folder
A curated list of awesome papers for Semantic Retrieval (TOIS Accepted: Semantic Models for the First-stage Retrieval: A Comprehensive Review).
A curated list of awesome papers for Semantic Retrieval (TOIS Accepted: Semantic Models for the First-stage Retrieval: A Comprehensive Review).
Latent Execution for Neural Program Synthesis
Latent Execution for Neural Program Synthesis This repo provides the code to replicate the experiments in the paper Xinyun Chen, Dawn Song, Yuandong T
Codes for NeurIPS 2021 paper "Adversarial Neuron Pruning Purifies Backdoored Deep Models"
Adversarial Neuron Pruning Purifies Backdoored Deep Models Code for NeurIPS 2021 "Adversarial Neuron Pruning Purifies Backdoored Deep Models" by Dongx
Implementation of the Paper: "Parameterized Hypercomplex Graph Neural Networks for Graph Classification" by Tuan Le, Marco Bertolini, Frank Noé and Djork-Arné Clevert
Parameterized Hypercomplex Graph Neural Networks (PHC-GNNs) PHC-GNNs (Le et al., 2021): https://arxiv.org/abs/2103.16584 PHM Linear Layer Illustration
Code for database and frontend of webpage for Neural Fields in Visual Computing and Beyond.
Neural Fields in Visual Computing—Complementary Webpage This is based on the amazing MiniConf project from Hendrik Strobelt and Sasha Rush—thank you!
In the case of your data having only 1 channel while want to use timm models
timm_custom Description In the case of your data having only 1 channel while want to use timm models (with or without pretrained weights), run the fol
A concept I came up which ditches the idea of "layers" in a neural network.
Dynet A concept I came up which ditches the idea of "layers" in a neural network. Install Copy Dynet.py to your project. Run the example Install matpl
YOLOv4-v3 Training Automation API for Linux
This repository allows you to get started with training a state-of-the-art Deep Learning model with little to no configuration needed! You provide your labeled dataset or label your dataset using our BMW-LabelTool-Lite and you can start the training right away and monitor it in many different ways like TensorBoard or a custom REST API and GUI. NoCode training with YOLOv4 and YOLOV3 has never been so easy.
A model checker for verifying properties in epistemic models
Epistemic Model Checker This is a model checker for verifying properties in epistemic models. The goal of the model checker is to check for Pluralisti
GUI for TOAD-GAN, a PCG-ML algorithm for Token-based Super Mario Bros. Levels.
If you are using this code in your own project, please cite our paper: @inproceedings{awiszus2020toadgan, title={TOAD-GAN: Coherent Style Level Gene
Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.
Softlearning Softlearning is a deep reinforcement learning toolbox for training maximum entropy policies in continuous domains. The implementation is
Keyword spotting on Arm Cortex-M Microcontrollers
Keyword spotting for Microcontrollers This repository consists of the tensorflow models and training scripts used in the paper: Hello Edge: Keyword sp
Si Adek Keras is software VR dangerous object detection.
Si Adek Python Keras Sistem Informasi Deteksi Benda Berbahaya Keras Python. Version 1.0 Developed by Ananda Rauf Maududi. Developed date: 24 November
Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"
AdderNet: Do We Really Need Multiplications in Deep Learning? This code is a demo of CVPR 2020 paper AdderNet: Do We Really Need Multiplications in De
SpinalNet: Deep Neural Network with Gradual Input
SpinalNet: Deep Neural Network with Gradual Input This repository contains scripts for training different variations of the SpinalNet and its counterp
Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods
ADGC: Awesome Deep Graph Clustering ADGC is a collection of state-of-the-art (SOTA), novel deep graph clustering methods (papers, codes and datasets).
This repository contains several image-to-image translation models, whcih were tested for RGB to NIR image generation. The models are Pix2Pix, Pix2PixHD, CycleGAN and PointWise.
RGB2NIR_Experimental This repository contains several image-to-image translation models, whcih were tested for RGB to NIR image generation. The models
Code for text augmentation method leveraging large-scale language models
HyperMix Code for our paper GPT3Mix and conducting classification experiments using GPT-3 prompt-based data augmentation. Getting Started Installing P
TensorFlow port of PyTorch Image Models (timm) - image models with pretrained weights.
TensorFlow-Image-Models Introduction Usage Models Profiling License Introduction TensorfFlow-Image-Models (tfimm) is a collection of image models with
Official implementation of SIGIR'2021 paper: "Sequential Recommendation with Graph Neural Networks".
SURGE: Sequential Recommendation with Graph Neural Networks This is our TensorFlow implementation for the paper: Sequential Recommendation with Graph
Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
Official code of APHYNITY Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting (ICLR 2021, Oral) Yuan Yin*, Vincent Le Guen*
ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.
ChebLieNet: Invariant spectral graph NNs turned equivariant by Riemannian geometry on Lie groups Hugo Aguettaz, Erik J. Bekkers, Michaël Defferrard We
Official Codes for Graph Modularity:Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Neural Networks.
Dynamic-Graphs-Construction Official Codes for Graph Modularity:Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Ne
Efficient semidefinite bounds for multi-label discrete graphical models.
Low rank solvers #################################### benchmark/ : folder with the random instances used in the paper. ############################
This is the official PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".
Sharpness-aware Quantization for Deep Neural Networks This is the official repository for our paper: Sharpness-aware Quantization for Deep Neural Netw
Code Generation using a large neural network called GPT-J
CodeGenX is a Code Generation system powered by Artificial Intelligence! It is delivered to you in the form of a Visual Studio Code Extension and is Free and Open-source!
VGGVox models for Speaker Identification and Verification trained on the VoxCeleb (1 & 2) datasets
VGGVox models for speaker identification and verification This directory contains code to import and evaluate the speaker identification and verificat
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
Yolo v4, v3 and v2 for Windows and Linux (neural networks for object detection) Paper YOLO v4: https://arxiv.org/abs/2004.10934 Paper Scaled YOLO v4:
Code to reprudece NeurIPS paper: Accelerated Sparse Neural Training: A Provable and Efficient Method to Find N:M Transposable Masks
Accelerated Sparse Neural Training: A Provable and Efficient Method to FindN:M Transposable Masks Recently, researchers proposed pruning deep neural n
Code for DisCo: Remedy Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning
DisCo: Remedy Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning Pytorch Implementation for DisCo: Remedy Self-supervi
Self-Supervised Document-to-Document Similarity Ranking via Contextualized Language Models and Hierarchical Inference
Self-Supervised Document Similarity Ranking (SDR) via Contextualized Language Models and Hierarchical Inference This repo is the implementation for SD
This is a Blender 2.9 script for importing mixamo Models to Godot-3
Mixamo-To-Godot This is a Blender 2.9 script for importing mixamo Models to Godot-3 The script does the following things Imports the mixamo models fro
Delve is a Python package for analyzing the inference dynamics of your PyTorch model.
Delve is a Python package for analyzing the inference dynamics of your PyTorch model.
FasterAI: A library to make smaller and faster models with FastAI.
Fasterai fasterai is a library created to make neural network smaller and faster. It essentially relies on common compression techniques for networks
An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.
Welcome to AdaptNLP A high level framework and library for running, training, and deploying state-of-the-art Natural Language Processing (NLP) models
A library that integrates huggingface transformers with the world of fastai, giving fastai devs everything they need to train, evaluate, and deploy transformer specific models.
blurr A library that integrates huggingface transformers with version 2 of the fastai framework Install You can now pip install blurr via pip install
Creating multimodal multitask models
Fusion Brain Challenge The English version of the document can be found here. Обновления 01.11 Мы выкладываем пример данных, аналогичных private test
Towards Improving Embedding Based Models of Social Network Alignment via Pseudo Anchors
PSML paper: Towards Improving Embedding Based Models of Social Network Alignment via Pseudo Anchors PSML_IONE,PSML_ABNE,PSML_DEEPLINK,PSML_SNNA: numpy
Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF)
Graph Convolutional Gated Recurrent Neural Network (GCGRNN) Improved from Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF
Finetune SSL models for MOS prediction
Finetune SSL models for MOS prediction This is code for our paper under review for ICASSP 2022: "Generalization Ability of MOS Prediction Networks" Er
Feature-engine is a Python library with multiple transformers to engineer and select features for use in machine learning models.
Feature-engine is a Python library with multiple transformers to engineer and select features for use in machine learning models. Feature-engine's transformers follow scikit-learn's functionality with fit() and transform() methods to first learn the transforming parameters from data and then transform the data.
apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly.
Please consider citing the manuscript if you use apricot in your academic work! You can find more thorough documentation here. apricot implements subm
PyTorch code for Composing Partial Differential Equations with Physics-Aware Neural Networks
FInite volume Neural Network (FINN) This repository contains the PyTorch code for models, training, and testing, and Python code for data generation t
PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".
Sharpness-aware Quantization for Deep Neural Networks Recent Update 2021.11.23: We release the source code of SAQ. Setup the environments Clone the re
A PyTorch port of the Neural 3D Mesh Renderer
Neural 3D Mesh Renderer (CVPR 2018) This repo contains a PyTorch implementation of the paper Neural 3D Mesh Renderer by Hiroharu Kato, Yoshitaka Ushik
Deep and online learning with spiking neural networks in Python
Introduction The brain is the perfect place to look for inspiration to develop more efficient neural networks. One of the main differences with modern
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear
The purpose of this project is to share knowledge on how awesome Streamlit is and can be
Awesome Streamlit The fastest way to build Awesome Tools and Apps! Powered by Python! The purpose of this project is to share knowledge on how Awesome
Code to compute permutation and drop-column importances in Python scikit-learn models
Feature importances for scikit-learn machine learning models By Terence Parr and Kerem Turgutlu. See Explained.ai for more stuff. The scikit-learn Ran
Python library for interactive topic model visualization. Port of the R LDAvis package.
pyLDAvis Python library for interactive topic model visualization. This is a port of the fabulous R package by Carson Sievert and Kenny Shirley. pyLDA
A method that utilized Generative Adversarial Network (GAN) to interpret the black-box deep image classifier models by PyTorch.
A method that utilized Generative Adversarial Network (GAN) to interpret the black-box deep image classifier models by PyTorch.
Collection of in-progress libraries for entity neural networks.
ENN Incubator Collection of in-progress libraries for entity neural networks: Neural Network Architectures for Structured State Entity Gym: Abstractio
Detectron2 for Document Layout Analysis
Detectron2 trained on PubLayNet dataset This repo contains the training configurations, code and trained models trained on PubLayNet dataset using Det
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models. Solve a variety of tasks with pre-trained models or finetune them in
Naszilla is a Python library for neural architecture search (NAS)
A repository to compare many popular NAS algorithms seamlessly across three popular benchmarks (NASBench 101, 201, and 301). You can implement your ow
Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.
HAWQ: Hessian AWare Quantization HAWQ is an advanced quantization library written for PyTorch. HAWQ enables low-precision and mixed-precision uniform
Neural networks applied in recognizing guitar chords using python, AutoML.NET with C# and .NET Core
Chord Recognition Demo application The demo application is written in C# with .NETCore. As of July 9, 2020, the only version available is for windows
Resilience from Diversity: Population-based approach to harden models against adversarial attacks
Resilience from Diversity: Population-based approach to harden models against adversarial attacks Requirements To install requirements: pip install -r
This toolkit provides codes to download and pre-process the SLUE datasets, train the baseline models, and evaluate SLUE tasks.
slue-toolkit We introduce Spoken Language Understanding Evaluation (SLUE) benchmark. This toolkit provides codes to download and pre-process the SLUE
Learning Neural Painters Fast! using PyTorch and Fast.ai
The Joy of Neural Painting Learning Neural Painters Fast! using PyTorch and Fast.ai Blogpost with more details: The Joy of Neural Painting The impleme
Learning Versatile Neural Architectures by Propagating Network Codes
Learning Versatile Neural Architectures by Propagating Network Codes Mingyu Ding, Yuqi Huo, Haoyu Lu, Linjie Yang, Zhe Wang, Zhiwu Lu, Jingdong Wang,
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Score-Based Generative Modeling through Stochastic Differential Equations This repo contains a PyTorch implementation for the paper Score-Based Genera
Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation. Intel iHD GPU (iGPU) support. NVIDIA GPU (dGPU) support.
mtomo Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation.
This repo contains implementation of different architectures for emotion recognition in conversations.
Emotion Recognition in Conversations Updates 🔥 🔥 🔥 Date Announcements 03/08/2021 🎆 🎆 We have released a new dataset M2H2: A Multimodal Multiparty
Python package for missing-data imputation with deep learning
MIDASpy Overview MIDASpy is a Python package for multiply imputing missing data using deep learning methods. The MIDASpy algorithm offers significant
MICOM is a Python package for metabolic modeling of microbial communities
Welcome MICOM is a Python package for metabolic modeling of microbial communities currently developed in the Gibbons Lab at the Institute for Systems
Lacmus is a cross-platform application that helps to find people who are lost in the forest using computer vision and neural networks.
lacmus The program for searching through photos from the air of lost people in the forest using Retina Net neural nwtwork. The project is being develo
Official implementation of Neural Bellman-Ford Networks (NeurIPS 2021)
NBFNet: Neural Bellman-Ford Networks This is the official codebase of the paper Neural Bellman-Ford Networks: A General Graph Neural Network Framework
DeepHawkeye is a library to detect unusual patterns in images using features from pretrained neural networks
English | 简体ä¸ć–‡ Introduction DeepHawkeye is a library to detect unusual patterns in images using features from pretrained neural networks Reference Pat
A python package to manage the stored receiver-side Strain Green's Tensor (SGT) database of 3D background models and able to generate Green's function and synthetic waveform
A python package to manage the stored receiver-side Strain Green's Tensor (SGT) database of 3D background models and able to generate Green's function and synthetic waveform
Code for Discovering Topics in Long-tailed Corpora with Causal Intervention.
Code for Discovering Topics in Long-tailed Corpora with Causal Intervention ACL2021 Findings Usage 0. Prepare environment Requirements: python==3.6 te
A python module to create random networks using network models
networkgen A python module to create random networks using network models Usage $
This is Pygrr PolyArt, a program used for drawing custom Polygon models for your Pygrr project!
This is Pygrr PolyArt, a program used for drawing custom Polygon models for your Pygrr project!
Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).
Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).
A single model for shaping, creating, accessing, storing data within a Database
'db' within pydantic - A single model for shaping, creating, accessing, storing data within a Database Key Features Integrated Redis Caching Support A
How to use TensorLayer
How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay
AutoML library for deep learning
Official Website: autokeras.com AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras
Latex code for making neural networks diagrams
PlotNeuralNet Latex code for drawing neural networks for reports and presentation. Have a look into examples to see how they are made. Additionally, l
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX Foolbox is a Python li
Neural network graphs and training metrics for PyTorch, Tensorflow, and Keras.
HiddenLayer A lightweight library for neural network graphs and training metrics for PyTorch, Tensorflow, and Keras. HiddenLayer is simple, easy to ex
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •
This script runs neural style transfer against the provided content image.
Neural Style Transfer Content Style Output Description: This script runs neural style transfer against the provided content image. The content image m
Neural Scene Flow Fields using pytorch-lightning, with potential improvements
nsff_pl Neural Scene Flow Fields using pytorch-lightning. This repo reimplements the NSFF idea, but modifies several operations based on observation o
SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker.
SageMaker Python SDK SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. With the S
Keras Implementation of Neural Style Transfer from the paper "A Neural Algorithm of Artistic Style"
Neural Style Transfer & Neural Doodles Implementation of Neural Style Transfer from the paper A Neural Algorithm of Artistic Style in Keras 2.0+ INetw
DeepFaceLab fork which provides IPython Notebook to use DFL with Google Colab
DFL-Colab — DeepFaceLab fork for Google Colab This project provides you IPython Notebook to use DeepFaceLab with Google Colaboratory. You can create y
TensorFlow code and pre-trained models for BERT
BERT ***** New March 11th, 2020: Smaller BERT Models ***** This is a release of 24 smaller BERT models (English only, uncased, trained with WordPiece
Lab Materials for MIT 6.S191: Introduction to Deep Learning
This repository contains all of the code and software labs for MIT 6.S191: Introduction to Deep Learning! All lecture slides and videos are available