1770 Repositories
Python neural-textures Libraries
NeuTex: Neural Texture Mapping for Volumetric Neural Rendering
NeuTex: Neural Texture Mapping for Volumetric Neural Rendering Paper: https://arxiv.org/abs/2103.00762 Running Run on the provided DTU scene cd run ba
The project page of paper: Architecture disentanglement for deep neural networks [ICCV 2021, oral]
This is the project page for the paper: Architecture Disentanglement for Deep Neural Networks, Jie Hu, Liujuan Cao, Tong Tong, Ye Qixiang, ShengChuan
HALO: A Skeleton-Driven Neural Occupancy Representation for Articulated Hands
HALO: A Skeleton-Driven Neural Occupancy Representation for Articulated Hands Oral Presentation, 3DV 2021 Korrawe Karunratanakul, Adrian Spurr, Zicong
A TensorFlow implementation of Neural Program Synthesis from Diverse Demonstration Videos
ViZDoom http://vizdoom.cs.put.edu.pl ViZDoom allows developing AI bots that play Doom using only the visual information (the screen buffer). It is pri
End-2-end speech synthesis with recurrent neural networks
Introduction New: Interactive demo using Google Colaboratory can be found here TTS-Cube is an end-2-end speech synthesis system that provides a full p
PyTorch implementation of the Pose Residual Network (PRN)
Pose Residual Network This repository contains a PyTorch implementation of the Pose Residual Network (PRN) presented in our ECCV 2018 paper: Muhammed
Train neural network for semantic segmentation (deep lab V3) with pytorch in less then 50 lines of code
Train neural network for semantic segmentation (deep lab V3) with pytorch in 50 lines of code Train net semantic segmentation net using Trans10K datas
A single model that parses Universal Dependencies across 75 languages.
A single model that parses Universal Dependencies across 75 languages. Given a sentence, jointly predicts part-of-speech tags, morphology tags, lemmas, and dependency trees.
AAAI 2022: Stationary diffusion state neural estimation
Stationary Diffusion State Neural Estimation Although many graph-based clustering methods attempt to model the stationary diffusion state in their obj
Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle
DOC | Quick Start | 中文 Breaking News !! 🔥 🔥 🔥 OGB-LSC KDD CUP 2021 winners announced!! (2021.06.17) Super excited to announce our PGL team won TWO
Codebase for Inducing Causal Structure for Interpretable Neural Networks
Interchange Intervention Training (IIT) Codebase for Inducing Causal Structure for Interpretable Neural Networks Release Notes 12/01/2021: Code and Pa
PyTorch(Geometric) implementation of G^2GNN in "Imbalanced Graph Classification via Graph-of-Graph Neural Networks"
This repository is an official PyTorch(Geometric) implementation of G^2GNN in "Imbalanced Graph Classification via Graph-of-Graph Neural Networks". Th
[NeurIPS'21 Spotlight] PyTorch code for our paper "Aligned Structured Sparsity Learning for Efficient Image Super-Resolution"
ASSL This repository is for a new network pruning method (Aligned Structured Sparsity Learning, ASSL) for efficient single image super-resolution (SR)
Learning to Rewrite for Non-Autoregressive Neural Machine Translation
RewriteNAT This repo provides the code for reproducing our proposed RewriteNAT in EMNLP 2021 paper entitled "Learning to Rewrite for Non-Autoregressiv
Milano is a tool for automating hyper-parameters search for your models on a backend of your choice.
Milano (This is a research project, not an official NVIDIA product.) Documentation https://nvidia.github.io/Milano Milano (Machine learning autotuner
A light weight data augmentation tool for training CNNs and Viola Jones detectors
hey-daug A light weight data augmentation tool for training CNNs and Viola Jones detectors (Haar Cascades). This tool inflates your data by up to six
Convolutional Neural Networks
Darknet Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation. D
BERTAC (BERT-style transformer-based language model with Adversarially pretrained Convolutional neural network)
BERTAC (BERT-style transformer-based language model with Adversarially pretrained Convolutional neural network) BERTAC is a framework that combines a
Codebase for testing whether hidden states of neural networks encode discrete structures.
structural-probes Codebase for testing whether hidden states of neural networks encode discrete structures. Based on the paper A Structural Probe for
Multi-Task Deep Neural Networks for Natural Language Understanding
New Release We released Adversarial training for both LM pre-training/finetuning and f-divergence. Large-scale Adversarial training for LMs: ALUM code
A production-ready, scalable Indexer for the Jina neural search framework, based on HNSW and PSQL
🌟 HNSW + PostgreSQL Indexer HNSWPostgreSQLIndexer Jina is a production-ready, scalable Indexer for the Jina neural search framework. It combines the
DeepFill v1/v2 with Contextual Attention and Gated Convolution, CVPR 2018, and ICCV 2019 Oral
Generative Image Inpainting An open source framework for generative image inpainting task, with the support of Contextual Attention (CVPR 2018) and Ga
MXNet implementation for: Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
Octave Convolution MXNet implementation for: Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution Imag
A library for implementing Decentralized Graph Neural Network algorithms.
decentralized-gnn A package for implementing and simulating decentralized Graph Neural Network algorithms for classification of peer-to-peer nodes. De
Decoding the Protein-ligand Interactions Using Parallel Graph Neural Networks
Decoding the Protein-ligand Interactions Using Parallel Graph Neural Networks Requirements python 0.10+ rdkit 2020.03.3.0 biopython 1.78 openbabel 2.4
Codes and models of NeurIPS2021 paper - DominoSearch: Find layer-wise fine-grained N:M sparse schemes from dense neural networks
DominoSearch This is repository for codes and models of NeurIPS2021 paper - DominoSearch: Find layer-wise fine-grained N:M sparse schemes from dense n
Official PyTorch Implementation of HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning (NeurIPS 2021 Spotlight)
[NeurIPS 2021 Spotlight] HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning [Paper] This is Official PyTorch implementatio
Official implementation of Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models at NeurIPS 2021
Representer Point Selection via Local Jacobian Expansion for Classifier Explanation of Deep Neural Networks and Ensemble Models This repository is the
Using Random Effects to Account for High-Cardinality Categorical Features and Repeated Measures in Deep Neural Networks
LMMNN Using Random Effects to Account for High-Cardinality Categorical Features and Repeated Measures in Deep Neural Networks This is the working dire
Discovering Dynamic Salient Regions with Spatio-Temporal Graph Neural Networks
Discovering Dynamic Salient Regions with Spatio-Temporal Graph Neural Networks This is the official code for DyReg model inroduced in Discovering Dyna
Probabilistic Tensor Decomposition of Neural Population Spiking Activity
Probabilistic Tensor Decomposition of Neural Population Spiking Activity Matlab (recommended) and Python (in developement) implementations of Soulat e
Pytorch implementation of the paper "Topic Modeling Revisited: A Document Graph-based Neural Network Perspective"
Graph Neural Topic Model (GNTM) This is the pytorch implementation of the paper "Topic Modeling Revisited: A Document Graph-based Neural Network Persp
Toolbox to analyze temporal context invariance of deep neural networks
PyTCI A toolbox that estimates the integration window of a sensory response using the "Temporal Context Invariance" paradigm (TCI). The TCI method Int
Representing Long-Range Context for Graph Neural Networks with Global Attention
Graph Augmentation Graph augmentation/self-supervision/etc. Algorithms gcn gcn+virtual node gin gin+virtual node PNA GraphTrans Augmentation methods N
Code for 2021 NeurIPS --- Towards Multi-Grained Explainability for Graph Neural Networks
ReFine: Multi-Grained Explainability for GNNs We are trying hard to update the code, but it may take a while to complete due to our tight schedule rec
The official implementation of EIGNN: Efficient Infinite-Depth Graph Neural Networks (NeurIPS 2021)
EIGNN: Efficient Infinite-Depth Graph Neural Networks The official implementation of EIGNN: Efficient Infinite-Depth Graph Neural Networks (NeurIPS 20
The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021
Directed Graph Contrastive Learning Paper | Poster | Supplementary The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL). In this
Discerning Decision-Making Process of Deep Neural Networks with Hierarchical Voting Transformation
Configurations Change HOME_PATH in CONFIG.py as the current path Data Prepare CENSINCOME Download data Put census-income.data and census-income.test i
Official implementation of the NeurIPS 2021 paper Online Learning Of Neural Computations From Sparse Temporal Feedback
Online Learning Of Neural Computations From Sparse Temporal Feedback This repository is the official implementation of the NeurIPS 2021 paper Online L
Code for models used in Bashiri et al., "A Flow-based latent state generative model of neural population responses to natural images".
A Flow-based latent state generative model of neural population responses to natural images Code for "A Flow-based latent state generative model of ne
NeurIPS-2021: Neural Auto-Curricula in Two-Player Zero-Sum Games.
NAC Official PyTorch implementation of NAC from the paper: Neural Auto-Curricula in Two-Player Zero-Sum Games. We release code for: Gradient based ora
A simple and useful implementation of LPIPS.
lpips-pytorch Description Developing perceptual distance metrics is a major topic in recent image processing problems. LPIPS[1] is a state-of-the-art
Official implementation of "Robust channel-wise illumination estimation"
This repository provides the official implementation of "Robust channel-wise illumination estimation." accepted in BMVC (2021).
Higher quality textures for the Metal Gear Solid series.
Metal Gear Solid: HD Textures Higher quality textures for the Metal Gear Solid series. The goal is to maximize the quality of assets that the engine w
Implementation of Artificial Neural Network Algorithm
Artificial Neural Network This repository contain implementation of Artificial Neural Network Algorithm in several programming languanges and framewor
Various Algorithms for Short Text Mining
Short Text Mining in Python Introduction This package shorttext is a Python package that facilitates supervised and unsupervised learning for short te
Adjusting for Autocorrelated Errors in Neural Networks for Time Series
Adjusting for Autocorrelated Errors in Neural Networks for Time Series This repository is the official implementation of the paper "Adjusting for Auto
Long Expressive Memory (LEM)
Long Expressive Memory for Sequence Modeling This repository contains the implementation to reproduce the numerical experiments of the paper Long Expr
Fully convolutional deep neural network to remove transparent overlays from images
Fully convolutional deep neural network to remove transparent overlays from images
Code for CVPR 2021 paper TransNAS-Bench-101: Improving Transferrability and Generalizability of Cross-Task Neural Architecture Search.
TransNAS-Bench-101 This repository contains the publishable code for CVPR 2021 paper TransNAS-Bench-101: Improving Transferrability and Generalizabili
A benchmark dataset for emulating atmospheric radiative transfer in weather and climate models with machine learning (NeurIPS 2021 Datasets and Benchmarks Track)
ClimART - A Benchmark Dataset for Emulating Atmospheric Radiative Transfer in Weather and Climate Models Official PyTorch Implementation Using deep le
This is a JAX implementation of Neural Radiance Fields for learning purposes.
learn-nerf This is a JAX implementation of Neural Radiance Fields for learning purposes. I've been curious about NeRF and its follow-up work for a whi
Data and evaluation code for the paper WikiNEuRal: Combined Neural and Knowledge-based Silver Data Creation for Multilingual NER (EMNLP 2021).
Data and evaluation code for the paper WikiNEuRal: Combined Neural and Knowledge-based Silver Data Creation for Multilingual NER. @inproceedings{tedes
Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics.
Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics. By Andres Milioto @ University of Bonn. (for the new P
PyTorch implementation for the Neuro-Symbolic Sudoku Solver leveraging the power of Neural Logic Machines (NLM)
Neuro-Symbolic Sudoku Solver PyTorch implementation for the Neuro-Symbolic Sudoku Solver leveraging the power of Neural Logic Machines (NLM). Please n
A real world application of a Recurrent Neural Network on a binary classification of time series data
What is this This is a real world application of a Recurrent Neural Network on a binary classification of time series data. This project includes data
Official implementation of "Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks", NeurIPS 2021.
PHDimGeneralization Official implementation of "Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks", NeurIPS 2021. Overvie
Subnet Replacement Attack: Towards Practical Deployment-Stage Backdoor Attack on Deep Neural Networks
Subnet Replacement Attack: Towards Practical Deployment-Stage Backdoor Attack on Deep Neural Networks Official implementation of paper Towards Practic
Codes for paper "KNAS: Green Neural Architecture Search"
KNAS Codes for paper "KNAS: Green Neural Architecture Search" KNAS is a green (energy-efficient) Neural Architecture Search (NAS) approach. It contain
A framework that constructs deep neural networks, autoencoders, logistic regressors, and linear networks
A framework that constructs deep neural networks, autoencoders, logistic regressors, and linear networks without the use of any outside machine learning libraries - all from scratch.
Large scale and asynchronous Hyperparameter Optimization at your fingertip.
Syne Tune This package provides state-of-the-art distributed hyperparameter optimizers (HPO) where trials can be evaluated with several backend option
PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)
PointCNN: Convolution On X-Transformed Points Created by Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen. Introduction PointCNN
Training open neural machine translation models
Train Opus-MT models This package includes scripts for training NMT models using MarianNMT and OPUS data for OPUS-MT. More details are given in the Ma
PyTorch version repo for CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes
Study-CSRNet-pytorch This is the PyTorch version repo for CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes
Multi-view 3D reconstruction using neural rendering. Unofficial implementation of UNISURF, VolSDF, NeuS and more.
Volume rendering + 3D implicit surface Showcase What? previous: surface rendering; now: volume rendering previous: NeRF's volume density; now: implici
Haystack is an open source NLP framework that leverages Transformer models.
Haystack is an end-to-end framework that enables you to build powerful and production-ready pipelines for different search use cases. Whether you want
Pytorch and Keras Implementations of Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects.
The repository contains the implementations for Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects. Model
A simple and extensible library to create Bayesian Neural Network layers on PyTorch.
Blitz - Bayesian Layers in Torch Zoo BLiTZ is a simple and extensible library to create Bayesian Neural Network Layers (based on whats proposed in Wei
Pytorch implementation of NeurIPS 2021 paper: Geometry Processing with Neural Fields.
Geometry Processing with Neural Fields Pytorch implementation for the NeurIPS 2021 paper: Geometry Processing with Neural Fields Guandao Yang, Serge B
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
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
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,
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
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
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!
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.
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
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).
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
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
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!
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
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.
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
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