2409 Repositories
Python keras-neural-networks Libraries
With Py-Autocrack you can crack WPA2 networks in no time.
With Py-Autocrack you can crack WPA2 networks in no time. All based on Aircrack-ng and Crunch.
DiffWave is a fast, high-quality neural vocoder and waveform synthesizer.
DiffWave DiffWave is a fast, high-quality neural vocoder and waveform synthesizer. It starts with Gaussian noise and converts it into speech via itera
Noise Conditional Score Networks (NeurIPS 2019, Oral)
Generative Modeling by Estimating Gradients of the Data Distribution This repo contains the official implementation for the NeurIPS 2019 paper Generat
A Loss Function for Generative Neural Networks Based on Watson’s Perceptual Model
This repository contains the similarity metrics designed and evaluated in the paper, and instructions and code to re-run the experiments. Implementation in the deep-learning framework PyTorch
MoViNets PyTorch implementation: Mobile Video Networks for Efficient Video Recognition;
MoViNet-pytorch Pytorch unofficial implementation of MoViNets: Mobile Video Networks for Efficient Video Recognition. Authors: Dan Kondratyuk, Liangzh
Neural HMMs are all you need (for high-quality attention-free TTS)
Neural HMMs are all you need (for high-quality attention-free TTS) Shivam Mehta, Éva Székely, Jonas Beskow, and Gustav Eje Henter This is the official
Source code for our paper "Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures"
Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures Code for the Multiplex Molecular Graph Neural Network (M
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
Spatial Temporal Graph Convolutional Networks (ST-GCN) for Skeleton-Based Action Recognition in PyTorch
Reminder ST-GCN has transferred to MMSkeleton, and keep on developing as an flexible open source toolbox for skeleton-based human understanding. You a
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.
PyTorch implementation for "HyperSPNs: Compact and Expressive Probabilistic Circuits", NeurIPS 2021
HyperSPN This repository contains code for the paper: HyperSPNs: Compact and Expressive Probabilistic Circuits "HyperSPNs: Compact and Expressive Prob
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)
Palo Alto Networks PAN-OS SDK for Python
Palo Alto Networks PAN-OS SDK for Python The PAN-OS SDK for Python (pan-os-python) is a package to help interact with Palo Alto Networks devices (incl
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
Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks
Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks Contributions A novel pairwise feature LSP to extract structural
Another pytorch implementation of FCN (Fully Convolutional Networks)
FCN-pytorch-easiest Trying to be the easiest FCN pytorch implementation and just in a get and use fashion Here I use a handbag semantic segmentation f
An example of semantic segmentation using tensorflow in eager execution.
Semantic segmentation using Tensorflow eager execution Requirement Python 2.7+ Tensorflow-gpu OpenCv H5py Scikit-learn Numpy Imgaug Train with eager e
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
Code & Models for Temporal Segment Networks (TSN) in ECCV 2016
Temporal Segment Networks (TSN) We have released MMAction, a full-fledged action understanding toolbox based on PyTorch. It includes implementation fo
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
DenseNet Implementation in Keras with ImageNet Pretrained Models
DenseNet-Keras with ImageNet Pretrained Models This is an Keras implementation of DenseNet with ImageNet pretrained weights. The weights are converted
Reproduce ResNet-v2(Identity Mappings in Deep Residual Networks) with MXNet
Reproduce ResNet-v2 using MXNet Requirements Install MXNet on a machine with CUDA GPU, and it's better also installed with cuDNN v5 Please fix the ran
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
Code for this paper The Lottery Ticket Hypothesis for Pre-trained BERT Networks.
The Lottery Ticket Hypothesis for Pre-trained BERT Networks Code for this paper The Lottery Ticket Hypothesis for Pre-trained BERT Networks. [NeurIPS
Implementation of Continuous Sparsification, a method for pruning and ticket search in deep networks
Continuous Sparsification Implementation of Continuous Sparsification (CS), a method based on l_0 regularization to find sparse neural networks, propo
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
[KBS] Aspect-based sentiment analysis via affective knowledge enhanced graph convolutional networks
#Sentic GCN Introduction This repository was used in our paper: Aspect-Based Sentiment Analysis via Affective Knowledge Enhanced Graph Convolutional N
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
Multi-path load balancing is a method used by most of the real-time network to split the packets into different paths rather than transferring it through a single path
Multipath-Load-Balancing Method of managing incoming traffic by distributing and sharing load fairly among multiple routes from source to destination
Official Keras Implementation for UNet++ in IEEE Transactions on Medical Imaging and DLMIA 2018
UNet++: A Nested U-Net Architecture for Medical Image Segmentation UNet++ is a new general purpose image segmentation architecture for more accurate i
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
[3DV 2021] A Dataset-Dispersion Perspective on Reconstruction Versus Recognition in Single-View 3D Reconstruction Networks
dispersion-score Official implementation of 3DV 2021 Paper A Dataset-dispersion Perspective on Reconstruction versus Recognition in Single-view 3D Rec
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
NeurIPS 2021 paper 'Representation Learning on Spatial Networks' code
Representation Learning on Spatial Networks This repository is the official implementation of Representation Learning on Spatial Networks. Training Ex
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
Robust & Reliable Route Recommendation on Road Networks
NeuroMLR: Robust & Reliable Route Recommendation on Road Networks This repository is the official implementation of NeuroMLR: Robust & Reliable Route
Official implementation of the NeurIPS'21 paper 'Conditional Generation Using Polynomial Expansions'.
Conditional Generation Using Polynomial Expansions Official implementation of the conditional image generation experiments as described on the NeurIPS
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).
A Python library for Deep Graph Networks
PyDGN Wiki Description This is a Python library to easily experiment with Deep Graph Networks (DGNs). It provides automatic management of data splitti
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
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
Mask R-CNN for Object Detection and Segmentation This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bound
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
A simple rest api serving a deep learning model that classifies human gender based on their faces. (vgg16 transfare learning)
this is a simple rest api serving a deep learning model that classifies human gender based on their faces. (vgg16 transfare learning)
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
Torch implementation of "Enhanced Deep Residual Networks for Single Image Super-Resolution"
NTIRE2017 Super-resolution Challenge: SNU_CVLab Introduction This is our project repository for CVPR 2017 Workshop (2nd NTIRE). We, Team SNU_CVLab, (B
A Pytorch implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE
SMU_pytorch A Pytorch Implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE arXiv https://arxiv.org/ab
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
Unsupervised Feature Ranking via Attribute Networks.
FRANe Unsupervised Feature Ranking via Attribute Networks (FRANe) converts a dataset into a network (graph) with nodes that correspond to the features
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
Learning from graph data using Keras
Steps to run = Download the cora dataset from this link : https://linqs.soe.ucsc.edu/data unzip the files in the folder input/cora cd code python eda
Image Super-Resolution Using Very Deep Residual Channel Attention Networks
Image Super-Resolution Using Very Deep Residual Channel Attention Networks
Keras Model Implementation Walkthrough
Keras Model Implementation Walkthrough
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