2556 Repositories
Python Delayed-cellular-neural-network Libraries
A Tensorflow implementation of the Text Conditioned Auxiliary Classifier Generative Adversarial Network for Generating Images from text descriptions
A Tensorflow implementation of the Text Conditioned Auxiliary Classifier Generative Adversarial Network for Generating Images from text descriptions
A simple interface for editing natural photos with generative neural networks.
Neural Photo Editor A simple interface for editing natural photos with generative neural networks. This repository contains code for the paper "Neural
Interactive Image Generation via Generative Adversarial Networks
iGAN: Interactive Image Generation via Generative Adversarial Networks Project | Youtube | Paper Recent projects: [pix2pix]: Torch implementation for
A DCGAN to generate anime faces using custom mined dataset
Anime-Face-GAN-Keras A DCGAN to generate anime faces using custom dataset in Keras. Dataset The dataset is created by crawling anime database websites
Learning Chinese Character style with conditional GAN
zi2zi: Master Chinese Calligraphy with Conditional Adversarial Networks Introduction Learning eastern asian language typefaces with GAN. zi2zi(ๅญๅฐๅญ, me
Some tentative models that incorporate label propagation to graph neural networks for graph representation learning in nodes, links or graphs.
Some tentative models that incorporate label propagation to graph neural networks for graph representation learning in nodes, links or graphs.
๐ Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
Image Super-Resolution (ISR) The goal of this project is to upscale and improve the quality of low resolution images. This project contains Keras impl
Curated list of awesome GAN applications and demo
gans-awesome-applications Curated list of awesome GAN applications and demonstrations. Note: General GAN papers targeting simple image generation such
A list of all named GANs!
The GAN Zoo Every week, new GAN papers are coming out and it's hard to keep track of them all, not to mention the incredibly creative ways in which re
Build Graph Nets in Tensorflow
Graph Nets library Graph Nets is DeepMind's library for building graph networks in Tensorflow and Sonnet. Contact [email protected] for comments a
Hummingbird compiles trained ML models into tensor computation for faster inference.
Hummingbird Introduction Hummingbird is a library for compiling trained traditional ML models into tensor computations. Hummingbird allows users to se
PyClustering is a Python, C++ data mining library.
pyclustering is a Python, C++ data mining library (clustering algorithm, oscillatory networks, neural networks). The library provides Python and C++ implementations (C++ pyclustering library) of each algorithm or model. C++ pyclustering library is a part of pyclustering and supported for Linux, Windows and MacOS operating systems.
MiniSom is a minimalistic implementation of the Self Organizing Maps
MiniSom Self Organizing Maps MiniSom is a minimalistic and Numpy based implementation of the Self Organizing Maps (SOM). SOM is a type of Artificial N
Computations and statistics on manifolds with geometric structures.
Geomstats Code Continuous Integration Code coverage (numpy) Code coverage (autograd, tensorflow, pytorch) Documentation Community NEWS: Geomstats is r
Sequence to Sequence (seq2seq) Recurrent Neural Network (RNN) for Time Series Forecasting
Sequence to Sequence (seq2seq) Recurrent Neural Network (RNN) for Time Series Forecasting Note: You can find here the accompanying seq2seq RNN forecas
An implementation of a sequence to sequence neural network using an encoder-decoder
Keras implementation of a sequence to sequence model for time series prediction using an encoder-decoder architecture. I created this post to share a
Self-supervised Multi-modal Hybrid Fusion Network for Brain Tumor Segmentation
JBHI-Pytorch This repository contains a reference implementation of the algorithms described in our paper "Self-supervised Multi-modal Hybrid Fusion N
Official implementation for "Image Quality Assessment using Contrastive Learning"
Image Quality Assessment using Contrastive Learning Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli and Alan C. Bovik This is the offi
Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder
Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder
DeepMReye: magnetic resonance-based eye tracking using deep neural networks
DeepMReye: magnetic resonance-based eye tracking using deep neural networks
Implementation of the master's thesis "Temporal copying and local hallucination for video inpainting".
Temporal copying and local hallucination for video inpainting This repository contains the implementation of my master's thesis "Temporal copying and
Pytorch implementation of forward and inverse Haar Wavelets 2D
Pytorch implementation of forward and inverse Haar Wavelets 2D
[NeurIPS 2021] Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data
Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data (NeurIPS 2021) This repository will provide the official PyTorch implementa
Session-aware Item-combination Recommendation with Transformer Network
Session-aware Item-combination Recommendation with Transformer Network 2nd place (0.39224) code and report for IEEE BigData Cup 2021 Track1 Report EDA
Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization
Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization This repository contains the source code for the paper (link wi
Generating Band-Limited Adversarial Surfaces Using Neural Networks
Generating Band-Limited Adversarial Surfaces Using Neural Networks This is the official repository of the technical report that was published on arXiv
Fast Axiomatic Attribution for Neural Networks (NeurIPS*2021)
Fast Axiomatic Attribution for Neural Networks This is the official repository accompanying the NeurIPS 2021 paper: R. Hesse, S. Schaub-Meyer, and S.
Predict halo masses from simulations via graph neural networks
HaloGraphNet Predict halo masses from simulations via Graph Neural Networks. Given a dark matter halo and its galaxies, creates a graph with informati
Implementation of neural class expression synthesizers
NCES Implementation of neural class expression synthesizers (NCES) Installation Clone this repository: https://github.com/ConceptLengthLearner/NCES.gi
Pansharpening by convolutional neural networks in the full resolution framework
Z-PNN: Zoom Pansharpening Neural Network Pansharpening by convolutional neural networks in the full resolution framework is a deep learning method for
Learning a mapping from images to psychological similarity spaces with neural networks.
LearningPsychologicalSpaces v0.1: v1.1: v1.2: v1.3: v1.4: v1.5: The code in this repository explores learning a mapping from images to psychological s
Official implementation of Meta-StyleSpeech and StyleSpeech
Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation Dongchan Min, Dong Bok Lee, Eunho Yang, and Sung Ju Hwang This is an official code
Nyx-Net: Network Fuzzing with Incremental Snapshots
Nyx-Net: Network Fuzzing with Incremental Snapshots Nyx-Net is fast full-VM snapshot fuzzer for complex network based targets. It's built upon kAFL, R
SASE : Self-Adaptive noise distribution network for Speech Enhancement with heterogeneous data of Cross-Silo Federated learning
SASE : Self-Adaptive noise distribution network for Speech Enhancement with heterogeneous data of Cross-Silo Federated learning We propose a SASE mode
An implementation of Group Fisher Pruning for Practical Network Compression based on pytorch and mmcv
FisherPruning-Pytorch An implementation of Group Fisher Pruning for Practical Network Compression based on pytorch and mmcv Main Functions Pruning f
Task-related Saliency Network For Few-shot learning
Task-related Saliency Network For Few-shot learning This is an official implementation in Tensorflow of TRSN. Abstract An essential cue of human wisdo
Short and long time series classification using convolutional neural networks
time-series-classification Short and long time series classification via convolutional neural networks In this project, we present a novel framework f
sktime companion package for deep learning based on TensorFlow
NOTE: sktime-dl is currently being updated to work correctly with sktime 0.6, and wwill be fully relaunched over the summer. The plan is Refactor and
ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels
ROCKET + MINIROCKET ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels. Data Mining and Knowledge D
A toolbox to iNNvestigate neural networks' predictions!
iNNvestigate neural networks! Table of contents Introduction Installation Usage and Examples More documentation Contributing Releases Introduction In
AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention
AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet buil
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
NNI Doc | ็ฎไฝไธญๆ NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture
Neural Architecture Search Powered by Swarm Intelligence ๐
Neural Architecture Search Powered by Swarm Intelligence ๐ DeepSwarm DeepSwarm is an open-source library which uses Ant Colony Optimization to tackle
Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification tasks
Uniformer - Pytorch Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification ta
๐ชโKnock Knock: Get notified when your training ends with only two additional lines of code
Knock Knock A small library to get a notification when your training is complete or when it crashes during the process with two additional lines of co
EZ graph is an easy to use AI solution that allows you to make and train your neural networks without a single line of code.
EZ-Graph EZ Graph is a GUI that allows users to make and train neural networks without writing a single line of code. Requirements python 3 pandas num
Code for the paper "PortraitNet: Real-time portrait segmentation network for mobile device" @ CAD&Graphics2019
PortraitNet Code for the paper "PortraitNet: Real-time portrait segmentation network for mobile device". @ CAD&Graphics 2019 Introduction We propose a
UPSNet: A Unified Panoptic Segmentation Network
UPSNet: A Unified Panoptic Segmentation Network Introduction UPSNet is initially described in a CVPR 2019 oral paper. Disclaimer This repository is te
PSANet: Point-wise Spatial Attention Network for Scene Parsing, ECCV2018.
PSANet: Point-wise Spatial Attention Network for Scene Parsing (in construction) by Hengshuang Zhao*, Yi Zhang*, Shu Liu, Jianping Shi, Chen Change Lo
Unofficial implementation of Fast-SCNN: Fast Semantic Segmentation Network
Fast-SCNN: Fast Semantic Segmentation Network Unofficial implementation of the model architecture of Fast-SCNN. Real-time Semantic Segmentation and mo
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation This repository contains the source code of our paper, ESPNet (acc
Dual Attention Network for Scene Segmentation (CVPR2019)
Dual Attention Network for Scene Segmentation(CVPR2019) Jun Fu, Jing Liu, Haijie Tian, Yong Li, Yongjun Bao, Zhiwei Fang,and Hanqing Lu Introduction W
Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation
Attention Gated Networks (Image Classification & Segmentation) Pytorch implementation of attention gates used in U-Net and VGG-16 models. The framewor
Understanding Convolution for Semantic Segmentation
TuSimple-DUC by Panqu Wang, Pengfei Chen, Ye Yuan, Ding Liu, Zehua Huang, Xiaodi Hou, and Garrison Cottrell. Introduction This repository is for Under
Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)
Learning to Adapt Structured Output Space for Semantic Segmentation Pytorch implementation of our method for adapting semantic segmentation from the s
Tensorflow implementation of "Learning Deconvolution Network for Semantic Segmentation"
Tensorflow implementation of Learning Deconvolution Network for Semantic Segmentation. Install Instructions Works with tensorflow 1.11.0 and uses the
DeconvNet : Learning Deconvolution Network for Semantic Segmentation
DeconvNet: Learning Deconvolution Network for Semantic Segmentation Created by Hyeonwoo Noh, Seunghoon Hong and Bohyung Han at POSTECH Acknowledgement
TensorFlow-based implementation of "Pyramid Scene Parsing Network".
PSPNet_tensorflow Important Code is fine for inference. However, the training code is just for reference and might be only used for fine-tuning. If yo
PSPNet in Chainer
PSPNet This is an unofficial implementation of Pyramid Scene Parsing Network (PSPNet) in Chainer. Training Requirement Python 3.4.4+ Chainer 3.0.0b1+
Pyramid Scene Parsing Network, CVPR2017.
Pyramid Scene Parsing Network by Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, Jiaya Jia, details are in project page. Introduction This
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
Multipath RefineNet A MATLAB based framework for semantic image segmentation and general dense prediction tasks on images. This is the source code for
Fully Convolutional DenseNet (A.K.A 100 layer tiramisu) for semantic segmentation of images implemented in TensorFlow.
FC-DenseNet-Tensorflow This is a re-implementation of the 100 layer tiramisu, technically a fully convolutional DenseNet, in TensorFlow (Tiramisu). Th
LinkNet - This repository contains our Torch7 implementation of the network developed by us at e-Lab.
LinkNet This repository contains our Torch7 implementation of the network developed by us at e-Lab. You can go to our blogpost or read the article Lin
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation.
ENet This work has been published in arXiv: ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. Packages: train contains too
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
ENet in Caffe Execution times and hardware requirements Network 1024x512 1280x720 Parameters Model size (fp32) ENet 20.4 ms 32.9 ms 0.36 M 1.5 MB SegN
A playable implementation of Fully Convolutional Networks with Keras.
keras-fcn A re-implementation of Fully Convolutional Networks with Keras Installation Dependencies keras tensorflow Install with pip $ pip install git
My implementation of Fully Convolutional Neural Networks in Keras
Keras-FCN This repository contains my implementation of Fully Convolutional Networks in Keras (Tensorflow backend). Currently, semantic segmentation c
FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation
FCN_via_Keras FCN FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation. This
Torch implementation of SegNet and deconvolutional network
Torch implementation of SegNet and deconvolutional network
Retina blood vessel segmentation with a convolutional neural network
Retina blood vessel segmentation with a convolution neural network (U-net) This repository contains the implementation of a convolutional neural netwo
Generic U-Net Tensorflow implementation for image segmentation
Tensorflow Unet Warning This project is discontinued in favour of a Tensorflow 2 compatible reimplementation of this project found under https://githu
U-Net: Convolutional Networks for Biomedical Image Segmentation
Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras This tutorial shows how to use Keras library to build deep ne
Modification of convolutional neural net "UNET" for image segmentation in Keras framework
ZF_UNET_224 Pretrained Model Modification of convolutional neural net "UNET" for image segmentation in Keras framework Requirements Python 3.*, Keras
Code for our EMNLP 2021 paper โHeterogeneous Graph Neural Networks for Keyphrase Generationโ
GATER This repository contains the code for our EMNLP 2021 paper โHeterogeneous Graph Neural Networks for Keyphrase Generationโ. Our implementation is
Models Supported: AlbUNet [18, 34, 50, 101, 152] (1D and 2D versions for Single and Multiclass Segmentation, Feature Extraction with supports for Deep Supervision and Guided Attention)
AlbUNet-1D-2D-Tensorflow-Keras This repository contains 1D and 2D Signal Segmentation Model Builder for AlbUNet and several of its variants developed
Transformers and related deep network architectures are summarized and implemented here.
Transformers: from NLP to CV This is a practical introduction to Transformers from Natural Language Processing (NLP) to Computer Vision (CV) Introduct
[CVPR'20] TTSR: Learning Texture Transformer Network for Image Super-Resolution
TTSR Official PyTorch implementation of the paper Learning Texture Transformer Network for Image Super-Resolution accepted in CVPR 2020. Contents Intr
Interactive convnet features visualization for Keras
Quiver Interactive convnet features visualization for Keras The quiver workflow Video Demo Build your model in keras model = Model(...) Launch the vis
Neural network-based build time estimation for additive manufacturing
Neural network-based build time estimation for additive manufacturing Oh, Y., Sharp, M., Sprock, T., & Kwon, S. (2021). Neural network-based build tim
Codes for NeurIPS 2021 paper "On the Equivalence between Neural Network and Support Vector Machine".
On the Equivalence between Neural Network and Support Vector Machine Codes for NeurIPS 2021 paper "On the Equivalence between Neural Network and Suppo
NDE: Climate Modeling with Neural Diffusion Equation, ICDM'21
Climate Modeling with Neural Diffusion Equation Introduction This is the repository of our accepted ICDM 2021 paper "Climate Modeling with Neural Diff
Complex-Valued Neural Networks (CVNN)Complex-Valued Neural Networks (CVNN)
Complex-Valued Neural Networks (CVNN) Done by @NEGU93 - J. Agustin Barrachina Using this library, the only difference with a Tensorflow code is that y
Half Instance Normalization Network for Image Restoration
HINet Half Instance Normalization Network for Image Restoration, based on https://github.com/megvii-model/HINet. Dependencies NumPy PyTorch, preferabl
[NeurIPS 2021] Code for Learning Signal-Agnostic Manifolds of Neural Fields
Learning Signal-Agnostic Manifolds of Neural Fields This is the uncleaned code for the paper Learning Signal-Agnostic Manifolds of Neural Fields. The
Official PyTorch implementation of NAC from the paper: 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
Generative Art Using Neural Visual Grammars and Dual Encoders
Generative Art Using Neural Visual Grammars and Dual Encoders Arnheim 1 The original algorithm from the paper Generative Art Using Neural Visual Gramm
Implementation for the paper: Invertible Denoising Network: A Light Solution for Real Noise Removal (CVPR2021).
Invertible Image Denoising This is the PyTorch implementation of paper: Invertible Denoising Network: A Light Solution for Real Noise Removal (CVPR 20
This repo. is an implementation of ACFFNet, which is accepted for in Image and Vision Computing.
Attention-Guided-Contextual-Feature-Fusion-Network-for-Salient-Object-Detection This repo. is an implementation of ACFFNet, which is accepted for in I
Implementation of the bachelor's thesis "Real-time stock predictions with deep learning and news scraping".
Real-time stock predictions with deep learning and news scraping This repository contains a partial implementation of my bachelor's thesis "Real-time
An Advanced Local Network IP Scanner, made in python of course!
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ICS-Visualizer is an interactive Industrial Control Systems (ICS) network graph that contains up-to-date ICS metadata
ICS-Visualizer is an interactive Industrial Control Systems (ICS) network graph that contains up-to-date ICS metadata (Name, company, port, user manua
Code for "FPS-Net: A convolutional fusion network for large-scale LiDAR point cloud segmentation".
FPS-Net Code for "FPS-Net: A convolutional fusion network for large-scale LiDAR point cloud segmentation", accepted by ISPRS journal of Photogrammetry
A object detecting neural network powered by the yolo architecture and leveraging the PyTorch framework and associated libraries.
Yolo-Powered-Detector A object detecting neural network powered by the yolo architecture and leveraging the PyTorch framework and associated libraries
Investigating automatic navigation towards standard US views integrating MARL with the virtual US environment developed in CT2US simulation
AutomaticUSnavigation Investigating automatic navigation towards standard US views integrating MARL with the virtual US environment developed in CT2US
Physics-informed Neural Operator for Learning Partial Differential Equation
PINO Physics-informed Neural Operator for Learning Partial Differential Equation Abstract: Machine learning methods have recently shown promise in sol
An implementation of Equivariant e2 convolutional kernals into a convolutional self attention network, applied to radio astronomy data.
EquivariantSelfAttention An implementation of Equivariant e2 convolutional kernals into a convolutional self attention network, applied to radio astro
Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph Machine Learning.
Homepage | Paper | Datasets | Leaderboard | Documentation Graph Robustness Benchmark (GRB) provides scalable, unified, modular, and reproducible evalu
Kennedy Institute of Rheumatology University of Oxford Project November 2019
TradingBot6M Kennedy Institute of Rheumatology University of Oxford Project November 2019 Run Change api.txt to binance api key: https://www.binance.c
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
Readings for "A Unified View of Relational Deep Learning for Polypharmacy Side Effect, Combination Therapy, and Drug-Drug Interaction Prediction."
Polypharmacy - DDI - Synergy Survey The Survey Paper This repository accompanies our survey paper A Unified View of Relational Deep Learning for Polyp