1986 Repositories
Python Awesome-of-Neural-Rendering Libraries
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
ONNX Runtime is a cross-platform inference and training machine-learning accelerator. ONNX Runtime inference can enable faster customer experiences an
PyTorch implementation of Super SloMo by Jiang et al.
Super-SloMo PyTorch implementation of "Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation" by Jiang H., Sun
This repository contains the code for the paper Neural RGB-D Surface Reconstruction
Neural RGB-D Surface Reconstruction Paper | Project Page | Video Neural RGB-D Surface Reconstruction Dejan Azinović, Ricardo Martin-Brualla, Dan B Gol
A Deep Learning Framework for Neural Derivative Hedging
NNHedge NNHedge is a PyTorch based framework for Neural Derivative Hedging. The following repository was implemented to ease the experiments of our pa
Machine learning algorithms for many-body quantum systems
NetKet NetKet is an open-source project delivering cutting-edge methods for the study of many-body quantum systems with artificial neural networks and
StyleSwin: Transformer-based GAN for High-resolution Image Generation
StyleSwin This repo is the official implementation of "StyleSwin: Transformer-based GAN for High-resolution Image Generation". By Bowen Zhang, Shuyang
Official repository for "Deep Recurrent Neural Network with Multi-scale Bi-directional Propagation for Video Deblurring".
RNN-MBP Deep Recurrent Neural Network with Multi-scale Bi-directional Propagation for Video Deblurring (AAAI-2022) by Chao Zhu, Hang Dong, Jinshan Pan
A Japanese tokenizer based on recurrent neural networks
Nagisa is a python module for Japanese word segmentation/POS-tagging. It is designed to be a simple and easy-to-use tool. This tool has the following
Tensorflow Implementation for "Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition"
Tensorflow Implementation for "Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition" Pre-trained Deep Convo
Fast and Simple Neural Vocoder, the Multiband RNNMS
Multiband RNN_MS Fast and Simple vocoder, Multiband RNN_MS. Demo Quick training How to Use System Details Results References Demo ToDO: Link super gre
HNN: Human (Hollywood) Neural Network
HNN: Human (Hollywood) Neural Network Learn the top 1000 actors on IMDB with your very own low cost, highly parallel, CUDAless biological neural netwo
Code for Neural-GIF: Neural Generalized Implicit Functions for Animating People in Clothing(ICCV21)
NeuralGIF Code for Neural-GIF: Neural Generalized Implicit Functions for Animating People in Clothing(ICCV21) We present Neural Generalized Implicit F
Repository for GNSS-based position estimation using a Deep Neural Network
Code repository accompanying our work on 'Improving GNSS Positioning using Neural Network-based Corrections'. In this paper, we present a Deep Neural
This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CNPs), Neural Processes (NPs), Attentive Neural Processes (ANPs).
The Neural Process Family This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CN
Neural network for digit classification powered by cuda
cuda_nn_mnist Neural network library for digit classification powered by cuda Resources The library was built to work with MNIST dataset. python-mnist
Header-only library for using Keras models in C++.
frugally-deep Use Keras models in C++ with ease Table of contents Introduction Usage Performance Requirements and Installation FAQ Introduction Would
Implicit neural differentiable FM synthesizer
Implicit neural differentiable FM synthesizer The purpose of this project is to emulate arbitrary sounds with FM synthesis, where the parameters of th
CasualHealthcare's Pneumonia detection with Artificial Intelligence (Convolutional Neural Network)
CasualHealthcare's Pneumonia detection with Artificial Intelligence (Convolutional Neural Network) This is PneumoniaDiagnose, an artificially intellig
Code for 2021 NeurIPS --- Towards Multi-Grained Explainability for Graph Neural Networks
ReFine: Multi-Grained Explainability for GNNs This is the official code for Towards Multi-Grained Explainability for Graph Neural Networks (NeurIPS 20
Understanding the Properties of Minimum Bayes Risk Decoding in Neural Machine Translation.
Understanding Minimum Bayes Risk Decoding This repo provides code and documentation for the following paper: Müller and Sennrich (2021): Understanding
Supporting code for "Autoregressive neural-network wavefunctions for ab initio quantum chemistry".
naqs-for-quantum-chemistry This repository contains the codebase developed for the paper Autoregressive neural-network wavefunctions for ab initio qua
Tensorflow Tutorials using Jupyter Notebook
Tensorflow Tutorials using Jupyter Notebook TensorFlow tutorials written in Python (of course) with Jupyter Notebook. Tried to explain as kindly as po
Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
LSTMs for Human Activity Recognition Human Activity Recognition (HAR) using smartphones dataset and an LSTM RNN. Classifying the type of movement amon
Simple and ready-to-use tutorials for TensorFlow
TensorFlow World To support maintaining and upgrading this project, please kindly consider Sponsoring the project developer. Any level of support is a
TensorFlow tutorials and best practices.
Effective TensorFlow 2 Table of Contents Part I: TensorFlow 2 Fundamentals TensorFlow 2 Basics Broadcasting the good and the ugly Take advantage of th
TensorFlow (Python API) implementation of Neural Style
neural-style-tf This is a TensorFlow implementation of several techniques described in the papers: Image Style Transfer Using Convolutional Neural Net
A deep learning network built with TensorFlow and Keras to classify gender and estimate age.
Convolutional Neural Network (CNN). This repository contains a source code of a deep learning network built with TensorFlow and Keras to classify gend
NASH 2021 project... this may or may not end up working 🤷♂️
wavespace synthesiser this is my NASH 2021 project, which may or may not end up working 🤷♂️ what is going on? imagine you have a big folder of audio
A PyTorch based deep learning library for drug pair scoring.
Documentation | External Resources | Datasets | Examples ChemicalX is a deep learning library for drug-drug interaction, polypharmacy side effect and
Deep Reinforcement Learning for Keras.
Deep Reinforcement Learning for Keras What is it? keras-rl implements some state-of-the art deep reinforcement learning algorithms in Python and seaml
A curated list of resources dedicated to reinforcement learning applied to cyber security.
Awesome Reinforcement Learning for Cyber Security A curated list of resources dedicated to reinforcement learning applied to cyber security. Note that
A collection of resources on neural rendering.
awesome neural rendering A collection of resources on neural rendering. Contributing If you think I have missed out on something (or) have any suggest
Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying Lighting and SVBRDF From a Single Image
Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying Lighting and SVBRDF From a Single Image (Project page) Zhengqin Li, Mohammad Sha
InverseRenderNet: Learning single image inverse rendering, CVPR 2019.
InverseRenderNet: Learning single image inverse rendering !! Check out our new work InverseRenderNet++ paper and code, which improves the inverse rend
tensorflow code for inverse face rendering
InverseFaceRender This is tensorflow code for our project: Learning Inverse Rendering of Faces from Real-world Videos. (https://arxiv.org/abs/2003.120
Nvdiffrast - Modular Primitives for High-Performance Differentiable Rendering
Nvdiffrast – Modular Primitives for High-Performance Differentiable Rendering Modular Primitives for High-Performance Differentiable Rendering Samuli
A curated list of awesome neural radiance fields papers
Awesome Neural Radiance Fields A curated list of awesome neural radiance fields papers, inspired by awesome-computer-vision. How to submit a pull requ
[ICCV 2021] Our work presents a novel neural rendering approach that can efficiently reconstruct geometric and neural radiance fields for view synthesis.
MVSNeRF Project page | Paper This repository contains a pytorch lightning implementation for the ICCV 2021 paper: MVSNeRF: Fast Generalizable Radiance
Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes (CVPR 2021 Oral)
Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Surfaces Official code release for NGLOD. For technical details, please refer t
Learned Initializations for Optimizing Coordinate-Based Neural Representations
Learned Initializations for Optimizing Coordinate-Based Neural Representations Project Page | Paper Matthew Tancik*1, Ben Mildenhall*1, Terrance Wang1
O-CNN: Octree-based Convolutional Neural Networks for 3D Shape Analysis
O-CNN This repository contains the implementation of our papers related with O-CNN. The code is released under the MIT license. O-CNN: Octree-based Co
Open source code for the paper of Neural Sparse Voxel Fields.
Neural Sparse Voxel Fields (NSVF) Project Page | Video | Paper | Data Photo-realistic free-viewpoint rendering of real-world scenes using classical co
Official implementation of "Implicit Neural Representations with Periodic Activation Functions"
Implicit Neural Representations with Periodic Activation Functions Project Page | Paper | Data Vincent Sitzmann*, Julien N. P. Martel*, Alexander W. B
This repo contains code to reproduce all experiments in Equivariant Neural Rendering
Equivariant Neural Rendering This repo contains code to reproduce all experiments in Equivariant Neural Rendering by E. Dupont, M. A. Bautista, A. Col
Neural Contours: Learning to Draw Lines from 3D Shapes (CVPR2020)
Neural Contours: Learning to Draw Lines from 3D Shapes This repository contains the PyTorch implementation for CVPR 2020 Paper "Neural Contours: Learn
Official Pytorch implementation of Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations
Scene Representation Networks This is the official implementation of the NeurIPS submission "Scene Representation Networks: Continuous 3D-Structure-Aw
Training PyTorch models with differential privacy
Opacus is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the cli
Stable Neural ODE with Lyapunov-Stable Equilibrium Points for Defending Against Adversarial Attacks
Stable Neural ODE with Lyapunov-Stable Equilibrium Points for Defending Against Adversarial Attacks Stable Neural ODE with Lyapunov-Stable Equilibrium
Build Low Code Automated Tensorflow, What-IF explainable models in just 3 lines of code.
Build Low Code Automated Tensorflow explainable models in just 3 lines of code.
A Python library for rendering ASS subtitle file format using libass.
ass_renderer A Python library for rendering ASS subtitle file format using libass. Installation pip install --user ass-renderer Contributing # Clone
Almost State-of-the-art Text Generation library
Ps: we are adding transformer model soon Text Gen 🐐 Almost State-of-the-art Text Generation library Text gen is a python library that allow you build
Official code repository for "Exploring Neural Models for Query-Focused Summarization"
Query-Focused Summarization Official code repository for "Exploring Neural Models for Query-Focused Summarization" This is a work in progress. Expect
Codes for building and training the neural network model described in Domain-informed neural networks for interaction localization within astroparticle experiments.
Domain-informed Neural Networks Codes for building and training the neural network model described in Domain-informed neural networks for interaction
On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation (Findings of EMNLP 2021))
PTvsBT On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation (Findings of EMNLP 2021) Citation Please cite a
Pytorch implementation of our paper under review -- 1xN Pattern for Pruning Convolutional Neural Networks
1xN Pattern for Pruning Convolutional Neural Networks (paper) . This is Pytorch re-implementation of "1xN Pattern for Pruning Convolutional Neural Net
Code release of paper Improving neural implicit surfaces geometry with patch warping
NeuralWarp: Improving neural implicit surfaces geometry with patch warping Project page | Paper Code release of paper Improving neural implicit surfac
Training and Evaluation Code for Neural Volumes
Neural Volumes This repository contains training and evaluation code for the paper Neural Volumes. The method learns a 3D volumetric representation of
Code for "Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humans" CVPR 2021 best paper candidate
News 05/17/2021 To make the comparison on ZJU-MoCap easier, we save quantitative and qualitative results of other methods at here, including Neural Vo
Codebase for arXiv preprint "NeRF++: Analyzing and Improving Neural Radiance Fields"
NeRF++ Codebase for arXiv preprint "NeRF++: Analyzing and Improving Neural Radiance Fields" Work with 360 capture of large-scale unbounded scenes. Sup
Neural Point-Based Graphics
Neural Point-Based Graphics Project Video Paper Neural Point-Based Graphics Kara-Ali Aliev1 Artem Sevastopolsky1,2 Maria Kolos1,2 Dmitry Ulyanov3
Implementation of Nalbach et al. 2017 paper.
Deep Shading Convolutional Neural Networks for Screen-Space Shading Our project is based on Nalbach et al. 2017 paper. In this project, a set of buffe
🏃♀️ A curated list about human motion capture, analysis and synthesis.
Awesome Human Motion 🏃♀️ A curated list about human motion capture, analysis and synthesis. Contents Introduction Human Models Datasets Data Process
An end-to-end library for editing and rendering motion of 3D characters with deep learning [SIGGRAPH 2020]
Deep-motion-editing This library provides fundamental and advanced functions to work with 3D character animation in deep learning with Pytorch. The co
A simple, fast, and awesome discord nuke bot! The only thing you need to add is your bot token.
SimpleNukeBot A simple, fast, and awesome discord nuke bot! The only thing you need to add is your bot token. Instructions: All you need to do is crea
A simple Neural Network that predicts the label for a series of handwritten digits
Neural_Network A simple Neural Network that predicts the label for a series of handwritten numbers This program tries to predict the label (1,2,3 etc.
A Transformer-Based Feature Segmentation and Region Alignment Method For UAV-View Geo-Localization
University1652-Baseline [Paper] [Slide] [Explore Drone-view Data] [Explore Satellite-view Data] [Explore Street-view Data] [Video Sample] [中文介绍] This
Unofficial implementation of Google's FNet: Mixing Tokens with Fourier Transforms
FNet: Mixing Tokens with Fourier Transforms Pytorch implementation of Fnet : Mixing Tokens with Fourier Transforms. Citation: @misc{leethorp2021fnet,
Awesome Treasure of Transformers Models Collection
💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️
Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing
Notice: Support for Python 3.6 will be dropped in v.0.2.1, please plan accordingly! Efficient and Scalable Physics-Informed Deep Learning Collocation-
PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks
PyDEns PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks. With PyDEns one can solve PD
Physics-Informed Neural Networks (PINN) and Deep BSDE Solvers of Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
NeuralPDE NeuralPDE.jl is a solver package which consists of neural network solvers for partial differential equations using scientific machine learni
Sparse Physics-based and Interpretable Neural Networks
Sparse Physics-based and Interpretable Neural Networks for PDEs This repository contains the code and manuscript for research done on Sparse Physics-b
Implementation of Research Paper "Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation"
Zero-DCE and Zero-DCE++(Lite architechture for Mobile and edge Devices) Papers Abstract The paper presents a novel method, Zero-Reference Deep Curve E
Official implementation for Scale-Aware Neural Architecture Search for Multivariate Time Series Forecasting
1 SNAS4MTF This repo is the official implementation for Scale-Aware Neural Architecture Search for Multivariate Time Series Forecasting. 1.1 The frame
An implementation of quantum convolutional neural network with MindQuantum. Huawei, classifying MNIST dataset
关于实现的一点说明 山东大学 2020级 苏博南 www.subonan.com 文件说明 tools.py 这里面主要有两个函数: resize(a, lenb) 这其实是我找同学写的一个小算法hhh。给出一个$28\times 28$的方阵a,返回一个$lenb\times lenb$的方阵。因
A foreign language learning aid using a neural network to predict probability of translating foreign words
Langy Langy is a reading-focused foreign language learning aid orientated towards young children. Reading is an activity that every child knows. It is
Simple yet powerful CAD (Computer Aided Design) library, written with Python.
Py-MADCAD it's time to throw parametric softwares out ! Simple yet powerful CAD (Computer Aided Design) library, written with Python. Installation
This repository is the official implementation of the Hybrid Self-Attention NEAT algorithm.
This repository is the official implementation of the Hybrid Self-Attention NEAT algorithm. It contains the code to reproduce the results presented in the original paper: https://arxiv.org/abs/2112.03670
A web application using [FastAPI + streamlit + Docker] Neural Style Transfer (NST) refers to a class of software algorithms that manipulate digital images
Neural Style Transfer Web App - [FastAPI + streamlit + Docker] NST - application based on the Perceptual Losses for Real-Time Style Transfer and Super
A PaddlePaddle version of Neural Renderer, refer to its PyTorch version
Neural 3D Mesh Renderer in PadddlePaddle A PaddlePaddle version of Neural Renderer, refer to its PyTorch version Install Run: pip install neural-rende
An official source code for paper Deep Graph Clustering via Dual Correlation Reduction, accepted by AAAI 2022
Dual Correlation Reduction Network An official source code for paper Deep Graph Clustering via Dual Correlation Reduction, accepted by AAAI 2022. Any
[AAAI 2022] Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification
Sparse Structure Learning via Graph Neural Networks for inductive document classification Make graph dataset create co-occurrence graph for datasets.
A high-performance distributed deep learning system targeting large-scale and automated distributed training.
HETU Documentation | Examples Hetu is a high-performance distributed deep learning system targeting trillions of parameters DL model training, develop
Code for "Typilus: Neural Type Hints" PLDI 2020
Typilus A deep learning algorithm for predicting types in Python. Please find a preprint here. This repository contains its implementation (src/) and
AI4Good project for detecting waste in the environment
Detect waste AI4Good project for detecting waste in environment. www.detectwaste.ml. Our latest results were published in Waste Management journal in
The source code of the paper "SHGNN: Structure-Aware Heterogeneous Graph Neural Network"
SHGNN: Structure-Aware Heterogeneous Graph Neural Network The source code and dataset of the paper: SHGNN: Structure-Aware Heterogeneous Graph Neural
Some code of the implements of Geological Modeling Using 3D Pixel-Adaptive and Deformable Convolutional Neural Network
3D-GMPDCNN Geological Modeling Using 3D Pixel-Adaptive and Deformable Convolutional Neural Network PyTorch implementation of "Geological Modeling Usin
PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
PyGAD: Genetic Algorithm in Python PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine lear
Selecting Parallel In-domain Sentences for Neural Machine Translation Using Monolingual Texts
DataSelection-NMT Selecting Parallel In-domain Sentences for Neural Machine Translation Using Monolingual Texts Quick update: The paper got accepted o
Programming with Neural Surrogates of Programs
Programming with Neural Surrogates of Programs
Twin-deep neural network for semi-supervised learning of materials properties
Deep Semi-Supervised Teacher-Student Material Synthesizability Prediction Citation: Semi-supervised teacher-student deep neural network for materials
Centroid-UNet is deep neural network model to detect centroids from satellite images.
Centroid UNet - Locating Object Centroids in Aerial/Serial Images Introduction Centroid-UNet is deep neural network model to detect centroids from Aer
flask extension for integration with the awesome pydantic package
Flask-Pydantic Flask extension for integration of the awesome pydantic package with Flask. Installation python3 -m pip install Flask-Pydantic Basics U
PyG (PyTorch Geometric) - A library built upon PyTorch to easily write and train Graph Neural Networks (GNNs)
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data.
Official implementation of the article "Unsupervised JPEG Domain Adaptation For Practical Digital Forensics"
Unsupervised JPEG Domain Adaptation for Practical Digital Image Forensics @WIFS2021 (Montpellier, France) Rony Abecidan, Vincent Itier, Jeremie Boulan
Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks"
LUNAR Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks" Adam Goodge, Bryan Hooi, Ng See Kiong and
PyTorch implementation of normalizing flow models
PyTorch implementation of normalizing flow models
A PyTorch library and evaluation platform for end-to-end compression research
CompressAI CompressAI (compress-ay) is a PyTorch library and evaluation platform for end-to-end compression research. CompressAI currently provides: c
Sombra is simple Raytracer written in pure Python.
Sombra Sombra is simple Raytracer written in pure Python. It's main purpose is to help understand how raytracing works with a clean code. If you are l
wxPython's Project Phoenix. A new implementation of wxPython, better, stronger, faster than he was before.
wxPython Project Phoenix Introduction Welcome to wxPython's Project Phoenix! Phoenix is the improved next-generation wxPython, "better, stronger, fast