2213 Repositories
Python graph-neural-pde Libraries
Use graph-based analysis to re-classify stocks and to improve Markowitz portfolio optimization
Dynamic Stock Industrial Classification Use graph-based analysis to re-classify stocks and experiment different re-classification methodologies to imp
From Perceptron model to Deep Neural Network from scratch in Python.
Neural-Network-Basics Aim of this Repository: From Perceptron model to Deep Neural Network (from scratch) in Python. ** Currently working on a basic N
Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).
Weakly Supervised Segmentation with TensorFlow This repo contains a TensorFlow implementation of weakly supervised instance segmentation as described
Code of the paper "Part Detector Discovery in Deep Convolutional Neural Networks" by Marcel Simon, Erik Rodner and Joachim Denzler
Part Detector Discovery This is the code used in our paper "Part Detector Discovery in Deep Convolutional Neural Networks" by Marcel Simon, Erik Rodne
Film review classification
Film review classification Решение задачи классификации отзывов на фильмы на положительные и отрицательные с помощью рекуррентных нейронных сетей 1. З
Eff video representation - Efficient video representation through neural fields
Neural Residual Flow Fields for Efficient Video Representations 1. Download MPI
Dagon - An Asynchronous Task Graph Execution Engine
Dagon - An Asynchronous Task Graph Execution Engine Dagon is a job execution sys
Cryptocurrency Prediction with Artificial Intelligence (Deep Learning via LSTM Neural Networks)
Cryptocurrency Prediction with Artificial Intelligence (Deep Learning via LSTM Neural Networks)- Emirhan BULUT
Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras
Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras which will then be used to generate residuals
Food recognition model using convolutional neural network & computer vision
Food recognition model using convolutional neural network & computer vision. The goal is to match or beat the DeepFood Research Paper
A short and easy PyTorch implementation of E(n) Equivariant Graph Neural Networks
Simple implementation of Equivariant GNN A short implementation of E(n) Equivariant Graph Neural Networks for HOMO energy prediction. Just 50 lines of
Rede Neural Convolucional feita durante o processo seletivo do Laboratório de Inteligência Artificial da FACOM (UFMS)
Primeira_Rede_Neural_Convolucional Rede Neural Convolucional feita durante o processo seletivo do Laboratório de Inteligência Artificial da FACOM (UFM
This is the course project of AI3602: Data Mining of SJTU
This is the course project of AI3602: Data Mining of SJTU. Group Members include Jinghao Feng, Mingyang Jiang and Wenzhong Zheng.
A Python module for the generation and training of an entry-level feedforward neural network.
ff-neural-network A Python module for the generation and training of an entry-level feedforward neural network. This repository serves as a repurposin
Volsdf - Volume Rendering of Neural Implicit Surfaces
Volume Rendering of Neural Implicit Surfaces Project Page | Paper | Data This re
Atomistic Line Graph Neural Network
Table of Contents Introduction Installation Examples Pre-trained models Quick start using colab JARVIS-ALIGNN webapp Peformances on a few datasets Use
BERN2: an advanced neural biomedical namedentity recognition and normalization tool
BERN2 We present BERN2 (Advanced Biomedical Entity Recognition and Normalization), a tool that improves the previous neural network-based NER tool by
Code for ICCV 2021 paper Graph-to-3D: End-to-End Generation and Manipulation of 3D Scenes using Scene Graphs
Graph-to-3D This is the official implementation of the paper Graph-to-3d: End-to-End Generation and Manipulation of 3D Scenes Using Scene Graphs | arx
NeROIC: Neural Object Capture and Rendering from Online Image Collections
NeROIC: Neural Object Capture and Rendering from Online Image Collections This repository is for the source code for the paper NeROIC: Neural Object C
Code release for "MERLOT Reserve: Neural Script Knowledge through Vision and Language and Sound"
merlot_reserve Code release for "MERLOT Reserve: Neural Script Knowledge through Vision and Language and Sound" MERLOT Reserve (in submission) is a mo
This is RFA-Toolbox, a simple and easy-to-use library that allows you to optimize your neural network architectures using receptive field analysis (RFA) and create graph visualizations of your architecture.
ReceptiveFieldAnalysisToolbox This is RFA-Toolbox, a simple and easy-to-use library that allows you to optimize your neural network architectures usin
Intel® Neural Compressor is an open-source Python library running on Intel CPUs and GPUs
Intel® Neural Compressor targeting to provide unified APIs for network compression technologies, such as low precision quantization, sparsity, pruning, knowledge distillation, across different deep learning frameworks to pursue optimal inference performance.
This repo includes some graph-based CTR prediction models and other representative baselines.
Graph-based CTR prediction This is a repository designed for graph-based CTR prediction methods, it includes our graph-based CTR prediction methods: F
Mapping a variable-length sentence to a fixed-length vector using BERT model
Are you looking for X-as-service? Try the Cloud-Native Neural Search Framework for Any Kind of Data bert-as-service Using BERT model as a sentence enc
Keras implementations of Generative Adversarial Networks.
This repository has gone stale as I unfortunately do not have the time to maintain it anymore. If you would like to continue the development of it as
YoloV3 Implemented in Tensorflow 2.0
YoloV3 Implemented in TensorFlow 2.0 This repo provides a clean implementation of YoloV3 in TensorFlow 2.0 using all the best practices. Key Features
Python Machine Learning Jupyter Notebooks (ML website)
Python Machine Learning Jupyter Notebooks (ML website) Dr. Tirthajyoti Sarkar, Fremont, California (Please feel free to connect on LinkedIn here) Also
Practical Machine Learning with Python
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
Security audit Python project dependencies against security advisory databases.
Security audit Python project dependencies against security advisory databases.
A tiny, pedagogical neural network library with a pytorch-like API.
candl A tiny, pedagogical implementation of a neural network library with a pytorch-like API. The primary use of this library is for education. Use th
Finite-temperature variational Monte Carlo calculation of uniform electron gas using neural canonical transformation.
CoulombGas This code implements the neural canonical transformation approach to the thermodynamic properties of uniform electron gas. Building on JAX,
Pytorch implementation of our method for regularizing nerual radiance fields for few-shot neural volume rendering.
InfoNeRF: Ray Entropy Minimization for Few-Shot Neural Volume Rendering Pytorch implementation of our method for regularizing nerual radiance fields f
A Graph Neural Network Tool for Recovering Dense Sub-graphs in Random Dense Graphs.
PYGON A Graph Neural Network Tool for Recovering Dense Sub-graphs in Random Dense Graphs. Installation This code requires to install and run the graph
Neural network pruning for finding a sparse computational model for controlling a biological motor task.
MothPruning Scientific Overview Originally inspired by biological nervous systems, deep neural networks (DNNs) are powerful computational tools for mo
Classification of Long Sequential Data using Circular Dilated Convolutional Neural Networks
Classification of Long Sequential Data using Circular Dilated Convolutional Neural Networks arXiv preprint: https://arxiv.org/abs/2201.02143. Architec
Safe Control for Black-box Dynamical Systems via Neural Barrier Certificates
Safe Control for Black-box Dynamical Systems via Neural Barrier Certificates Installation Clone the repository: git clone https://github.com/Zengyi-Qi
BERN2: an advanced neural biomedical namedentity recognition and normalization tool
BERN2 We present BERN2 (Advanced Biomedical Entity Recognition and Normalization), a tool that improves the previous neural network-based NER tool by
Local cross-platform machine translation GUI, based on CTranslate2
DesktopTranslator Local cross-platform machine translation GUI, based on CTranslate2 Download Windows Installer You can either download a ready-made W
Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥
TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extens
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices
Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In
Code and data accompanying Natural Language Processing with PyTorch
Natural Language Processing with PyTorch Build Intelligent Language Applications Using Deep Learning By Delip Rao and Brian McMahan Welcome. This is a
Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 Tensorflow 2.0
NLP-Models-Tensorflow, Gathers machine learning and tensorflow deep learning models for NLP problems, code simplify inside Jupyter Notebooks 100%. Tab
🙄 Difficult algorithm, Simple code.
🎉TensorFlow2.0-Examples🎉! "Talk is cheap, show me the code." ----- Linus Torvalds Created by YunYang1994 This tutorial was designed for easily divin
A High-Quality Real Time Upscaler for Anime Video
Anime4K Anime4K is a set of open-source, high-quality real-time anime upscaling/denoising algorithms that can be implemented in any programming langua
Pure python implementations of popular ML algorithms.
Minimal ML algorithms This repo includes minimal implementations of popular ML algorithms using pure python and numpy. The purpose of these notebooks
Implementation of paper "DCS-Net: Deep Complex Subtractive Neural Network for Monaural Speech Enhancement"
DCS-Net This is the implementation of "DCS-Net: Deep Complex Subtractive Neural Network for Monaural Speech Enhancement" Steps to run the model Edit V
Official Implementation for Fast Training of Neural Lumigraph Representations using Meta Learning.
Fast Training of Neural Lumigraph Representations using Meta Learning Project Page | Paper | Data Alexander W. Bergman, Petr Kellnhofer, Gordon Wetzst
Official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR)
This is the official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment.
A simple version for graphfpn
GraphFPN: Graph Feature Pyramid Network for Object Detection Download graph-FPN-main.zip For training , run: python train.py For test with Graph_fpn
This is the official Pytorch-version code of FlatGCN (Flattened Graph Convolutional Networks for Recommendation).
FlatGCN This is the official Pytorch-version code of FlatGCN (Flattened Graph Convolutional Networks for Recommendation, submitted to ICASSP2022). Req
A Neural Network based chess engine and GUI made with Python and Tensorflow/Keras.
Haxaw-Chess Haxaw: Haxaw is the Neural Network based chess engine made with Python and Tensorflow/Keras. Also uses the python-chess library. (WIP: Imp
The VarCNN is an Convolution Neural Network based approach to automate Video Assistant Referee in football.
VarCnn: The Deep Learning Powered VAR
This application aims to read all wifi passwords and visualizes the complexity in graph formation by taking into account several criteria and help you generate new random passwords.
This application aims to read all wifi passwords and visualizes the complexity in graph formation by taking into account several criteria and help you generate new random passwords.
simple_pytorch_example project is a toy example of a python script that instantiates and trains a PyTorch neural network on the FashionMNIST dataset
simple_pytorch_example project is a toy example of a python script that instantiates and trains a PyTorch neural network on the FashionMNIST dataset
Neural-net-from-scratch - A simple Neural Network from scratch in Python using the Pymathrix library
A Simple Neural Network from scratch A Simple Neural Network from scratch in Pyt
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
LSTM Neural Network for Time Series Prediction LSTM built using the Keras Python package to predict time series steps and sequences. Includes sine wav
Fully Convlutional Neural Networks for state-of-the-art time series classification
Deep Learning for Time Series Classification As the simplest type of time series data, univariate time series provides a reasonably good starting poin
Deep Learning for Time Series Classification
Deep Learning for Time Series Classification This is the companion repository for our paper titled "Deep learning for time series classification: a re
Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.
Multilabel time series classification with LSTM Tensorflow implementation of model discussed in the following paper: Learning to Diagnose with LSTM Re
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection
Deep learning for time series forecasting Flow forecast is an open-source deep learning for time series forecasting framework. It provides all the lat
Demonstration of transfer of knowledge and generalization with distillation
Distilling-the-Knowledge-in-a-Neural-Network This is an implementation of a part of the paper "Distilling the Knowledge in a Neural Network" (https://
Elastic weight consolidation technique for incremental learning.
Overcoming-Catastrophic-forgetting-in-Neural-Networks Elastic weight consolidation technique for incremental learning. About Use this API if you dont
PyTorch implementation of the REMIND method from our ECCV-2020 paper "REMIND Your Neural Network to Prevent Catastrophic Forgetting"
REMIND Your Neural Network to Prevent Catastrophic Forgetting This is a PyTorch implementation of the REMIND algorithm from our ECCV-2020 paper. An ar
(JMLR' 19) A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
Python Outlier Detection (PyOD) Deployment & Documentation & Stats & License PyOD is a comprehensive and scalable Python toolkit for detecting outlyin
WTTE-RNN a framework for churn and time to event prediction
WTTE-RNN Weibull Time To Event Recurrent Neural Network A less hacky machine-learning framework for churn- and time to event prediction. Forecasting p
A Quick and Dirty Progressive Neural Network written in TensorFlow.
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Teaches a student network from the knowledge obtained via training of a larger teacher network
Distilling-the-knowledge-in-neural-network Teaches a student network from the knowledge obtained via training of a larger teacher network This is an i
A PyTorch implementation of the continual learning experiments with deep neural networks
Brain-Inspired Replay A PyTorch implementation of the continual learning experiments with deep neural networks described in the following paper: Brain
Cherche (search in French) allows you to create a neural search pipeline using retrievers and pre-trained language models as rankers.
Cherche (search in French) allows you to create a neural search pipeline using retrievers and pre-trained language models as rankers. Cherche is meant to be used with small to medium sized corpora. Cherche's main strength is its ability to build diverse and end-to-end pipelines.
Finite Element Analysis
FElupe - Finite Element Analysis FElupe is a Python 3.6+ finite element analysis package focussing on the formulation and numerical solution of nonlin
Datasets, tools, and benchmarks for representation learning of code.
The CodeSearchNet challenge has been concluded We would like to thank all participants for their submissions and we hope that this challenge provided
Creative Applications of Deep Learning w/ Tensorflow
Creative Applications of Deep Learning w/ Tensorflow This repository contains lecture transcripts and homework assignments as Jupyter Notebooks for th
GAT - Graph Attention Network (PyTorch) 💻 + graphs + 📣 = ❤️
GAT - Graph Attention Network (PyTorch) 💻 + graphs + 📣 = ❤️ This repo contains a PyTorch implementation of the original GAT paper ( 🔗 Veličković et
List of papers, code and experiments using deep learning for time series forecasting
Deep Learning Time Series Forecasting List of state of the art papers focus on deep learning and resources, code and experiments using deep learning f
Koç University deep learning framework.
Knet Knet (pronounced "kay-net") is the Koç University deep learning framework implemented in Julia by Deniz Yuret and collaborators. It supports GPU
Not Suitable for Work (NSFW) classification using deep neural network Caffe models.
Open nsfw model This repo contains code for running Not Suitable for Work (NSFW) classification deep neural network Caffe models. Please refer our blo
A list of NLP(Natural Language Processing) tutorials
NLP Tutorial A list of NLP(Natural Language Processing) tutorials built on PyTorch. Table of Contents A step-by-step tutorial on how to implement and
Pi-NAS: Improving Neural Architecture Search by Reducing Supernet Training Consistency Shift (ICCV 2021)
Π-NAS This repository provides the evaluation code of our submitted paper: Pi-NAS: Improving Neural Architecture Search by Reducing Supernet Training
Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21
Skeletal-GNN Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21 Various deep learning techniques have been propose
A new codebase for Group Activity Recognition. It contains codes for ICCV 2021 paper: Spatio-Temporal Dynamic Inference Network for Group Activity Recognition and some other methods.
Spatio-Temporal Dynamic Inference Network for Group Activity Recognition The source codes for ICCV2021 Paper: Spatio-Temporal Dynamic Inference Networ
Train Scene Graph Generation for Visual Genome and GQA in PyTorch = 1.2 with improved zero and few-shot generalization.
Scene Graph Generation Object Detections Ground truth Scene Graph Generated Scene Graph In this visualization, woman sitting on rock is a zero-shot tr
duralava is a neural network which can simulate a lava lamp in an infinite loop.
duralava duralava is a neural network which can simulate a lava lamp in an infinite loop. Example This is not a real lava lamp but a "fake" one genera
BERN2: an advanced neural biomedical namedentity recognition and normalization tool
BERN2 We present BERN2 (Advanced Biomedical Entity Recognition and Normalization
A library for graph deep learning research
Documentation | Paper [JMLR] | Tutorials | Benchmarks | Examples DIG: Dive into Graphs is a turnkey library for graph deep learning research. Why DIG?
A Telegram crawler to search groups and channels automatically and collect any type of data from them.
Introduction This is a crawler I wrote in Python using the APIs of Telethon months ago. This tool was not intended to be publicly available for a numb
Find graph motifs using intuitive notation
d o t m o t i f Find graph motifs using intuitive notation DotMotif is a library that identifies subgraphs or motifs in a large graph. It looks like t
Neural network for stock price prediction
neural_network_for_stock_price_prediction Neural networks for stock price predic
Supporting code for short YouTube series Neural Networks Demystified.
Neural Networks Demystified Supporting iPython notebooks for the YouTube Series Neural Networks Demystified. I've included formulas, code, and the tex
Machine Learning Study 혼자 해보기
Machine Learning Study 혼자 해보기 기여자 (Contributors) ✨ Teddy Lee 🏠 HongJaeKwon 🏠 Seungwoo Han 🏠 Tae Heon Kim 🏠 Steve Kwon 🏠 SW Song 🏠 K1A2 🏠 Wooil
Code for the Lovász-Softmax loss (CVPR 2018)
The Lovász-Softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks Maxim Berman, Amal Ranne
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models.
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.
Official Repsoitory for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]
Mish: Self Regularized Non-Monotonic Activation Function BMVC 2020 (Official Paper) Notes: (Click to expand) A considerably faster version based on CU
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Bayesian Neural Networks Pytorch implementations for the following approximate inference methods: Bayes by Backprop Bayes by Backprop + Local Reparame
Keras implementation of "One pixel attack for fooling deep neural networks" using differential evolution on Cifar10 and ImageNet
One Pixel Attack How simple is it to cause a deep neural network to misclassify an image if an attacker is only allowed to modify the color of one pix
This repository contains small projects related to Neural Networks and Deep Learning in general.
ILearnDeepLearning.py Description People say that nothing develops and teaches you like getting your hands dirty. This repository contains small proje
A general-purpose encoder-decoder framework for Tensorflow
READ THE DOCUMENTATION CONTRIBUTING A general-purpose encoder-decoder framework for Tensorflow that can be used for Machine Translation, Text Summariz
NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.
#NeuralTalk Warning: Deprecated. Hi there, this code is now quite old and inefficient, and now deprecated. I am leaving it on Github for educational p
TensorFlow implementation of AlexNet and its training and testing on ImageNet ILSVRC 2012 dataset
AlexNet training on ImageNet LSVRC 2012 This repository contains an implementation of AlexNet convolutional neural network and its training and testin
Convolutional Neural Networks for Sentence Classification
Convolutional Neural Networks for Sentence Classification Code for the paper Convolutional Neural Networks for Sentence Classification (EMNLP 2014). R
Code for paper "Multi-level Disentanglement Graph Neural Network"
Multi-level Disentanglement Graph Neural Network (MD-GNN) This is a PyTorch implementation of the MD-GNN, and the code includes the following modules: