1915 Repositories
Python neural-function-distributions Libraries
Source for the paper "Universal Activation Function for machine learning"
Universal Activation Function Tensorflow and Pytorch source code for the paper Yuen, Brosnan, Minh Tu Hoang, Xiaodai Dong, and Tao Lu. "Universal acti
DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks
What is DeepHyper? DeepHyper is a software package that uses learning, optimization, and parallel computing to automate the design and development of
Use unsupervised and supervised learning to predict stocks
AIAlpha: Multilayer neural network architecture for stock return prediction This project is meant to be an advanced implementation of stacked neural n
Introducing neural networks to predict stock prices
IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o
For specific function. For my own convenience. Remind owner to share data to another DITO user.
For specific function. For my own convenience. Remind owner to share data to another DITO user.
generate-2D-quadrilateral-mesh-with-neural-networks-and-tree-search
generate-2D-quadrilateral-mesh-with-neural-networks-and-tree-search This repository contains single-threaded TreeMesh code. I'm Hua Tong, a senior stu
Reference PyTorch implementation of "End-to-end optimized image compression with competition of prior distributions"
PyTorch reference implementation of "End-to-end optimized image compression with competition of prior distributions" by Benoit Brummer and Christophe
Code and experiments for "Deep Neural Networks for Rank Consistent Ordinal Regression based on Conditional Probabilities"
corn-ordinal-neuralnet This repository contains the orginal model code and experiment logs for the paper "Deep Neural Networks for Rank Consistent Ord
TYolov5: A Temporal Yolov5 Detector Based on Quasi-Recurrent Neural Networks for Real-Time Handgun Detection in Video
TYolov5: A Temporal Yolov5 Detector Based on Quasi-Recurrent Neural Networks for Real-Time Handgun Detection in Video Timely handgun detection is a cr
Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).
Fisher Induced Sparse uncHanging (FISH) Mask This repo contains the code for Fisher Induced Sparse uncHanging (FISH) Mask training, from "Training Neu
Unofficial implementation of Point-Unet: A Context-Aware Point-Based Neural Network for Volumetric Segmentation
Point-Unet This is an unofficial implementation of the MICCAI 2021 paper Point-Unet: A Context-Aware Point-Based Neural Network for Volumetric Segment
GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)
GemNet: Universal Directional Graph Neural Networks for Molecules Reference implementation in PyTorch of the geometric message passing neural network
TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.
TensorFlow GNN This is an early (alpha) release to get community feedback. It's under active development and we may break API compatibility in the fut
[ ICCV 2021 Oral ] Our method can estimate camera poses and neural radiance fields jointly when the cameras are initialized at random poses in complex scenarios (outside-in scenes, even with less texture or intense noise )
GNeRF This repository contains official code for the ICCV 2021 paper: GNeRF: GAN-based Neural Radiance Field without Posed Camera. This implementation
A stable algorithm for GAN training
DRAGAN (Deep Regret Analytic Generative Adversarial Networks) Link to our paper - https://arxiv.org/abs/1705.07215 Pytorch implementation (thanks!) -
PyTorch implementation for ComboGAN
ComboGAN This is our ongoing PyTorch implementation for ComboGAN. Code was written by Asha Anoosheh (built upon CycleGAN) [ComboGAN Paper] If you use
Single/multi view image(s) to voxel reconstruction using a recurrent neural network
3D-R2N2: 3D Recurrent Reconstruction Neural Network This repository contains the source codes for the paper Choy et al., 3D-R2N2: A Unified Approach f
Source code release of the paper: Knowledge-Guided Deep Fractal Neural Networks for Human Pose Estimation.
GNet-pose Project Page: http://guanghan.info/projects/guided-fractal/ UPDATE 9/27/2018: Prototxts and model that achieved 93.9Pck on LSP dataset. http
A TensorFlow Implementation of "Deep Multi-Scale Video Prediction Beyond Mean Square Error" by Mathieu, Couprie & LeCun.
Adversarial Video Generation This project implements a generative adversarial network to predict future frames of video, as detailed in "Deep Multi-Sc
SalGAN: Visual Saliency Prediction with Generative Adversarial Networks
SalGAN: Visual Saliency Prediction with Adversarial Networks Junting Pan Cristian Canton Ferrer Kevin McGuinness Noel O'Connor Jordi Torres Elisa Sayr
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
Learning Chinese Character style with conditional GAN
zi2zi: Master Chinese Calligraphy with Conditional Adversarial Networks Introduction Learning eastern asian language typefaces with GAN. zi2zi(字到字, me
A faster Python generator that get function results from multi-process workers
multiyield This package implements a Python generator that get function results from multi-process workers. The faster_fifo Queue (instead of the stan
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.
🔎 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
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
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se
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
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
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
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 | 简体中文 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 🐜
Neural Architecture Search Powered by Swarm Intelligence 🐜 DeepSwarm DeepSwarm is an open-source library which uses Ant Colony Optimization to tackle
🚪✊Knock 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
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
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
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+
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
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
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 “Heterogeneous Graph Neural Networks for Keyphrase Generation”
GATER This repository contains the code for our EMNLP 2021 paper “Heterogeneous Graph Neural Networks for Keyphrase Generation”. 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
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
[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
Tensorflow Implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE
SMU A Tensorflow Implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE arXiv https://arxiv.org/abs/211
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
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
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
Azure Neural Speech Service TTS
Written in Python using the Azure Speech SDK. App.py provides an easy way to create an Text-To-Speech request to Azure Speech and download the wav file. Azure Neural Voices Text-To-Speech enables fluid, natural-sounding text to speech that matches the patterns and intonation of human voices.
Pipetools enables function composition similar to using Unix pipes.
Pipetools Complete documentation pipetools enables function composition similar to using Unix pipes. It allows forward-composition and piping of arbit
An implementation of a discriminant function over a normal distribution to help classify datasets.
CS4044D Machine Learning Assignment 1 By Dev Sony, B180297CS The question, report and source code can be found here. Github Repo Solution 1 Based on t
Neural Articulated Radiance Field
Neural Articulated Radiance Field NARF Neural Articulated Radiance Field Atsuhiro Noguchi, Xiao Sun, Stephen Lin, Tatsuya Harada ICCV 2021 [Paper] [Co
Animatable Neural Radiance Fields for Modeling Dynamic Human Bodies
To make the comparison with Animatable NeRF easier on the Human3.6M dataset, we save the quantitative results at here, which also contains the results of other methods, including Neural Body, D-NeRF, Multi-view Neural Human Rendering, and Deferred Neural Human Rendering.
Neural Scene Flow Prior (NeurIPS 2021 spotlight)
Neural Scene Flow Prior Xueqian Li, Jhony Kaesemodel Pontes, Simon Lucey Will appear on Thirty-fifth Conference on Neural Information Processing Syste
Code for "NeRS: Neural Reflectance Surfaces for Sparse-View 3D Reconstruction in the Wild," in NeurIPS 2021
Code for Neural Reflectance Surfaces (NeRS) [arXiv] [Project Page] [Colab Demo] [Bibtex] This repo contains the code for NeRS: Neural Reflectance Surf
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
Code repo for "RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network" (Machine Learning and the Physical Sciences workshop in NeurIPS 2021).
RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network An official PyTorch implementation of the RBSRICNN network as desc
LSTM Neural Networks for Spectroscopic Studies of Type Ia Supernovae
Package Description The difficulties in acquiring spectroscopic data have been a major challenge for supernova surveys. snlstm is developed to provide
PyTorch implementation of Spiking Neural Networks trained on surrogate gradient & BPTT using snntorch.
snn-localization repo PyTorch implementation of Spiking Neural Networks trained on surrogate gradient & BPTT using snntorch. Install Dependencies Orig