4011 Repositories
Python deep-neural-networks Libraries
Official implementation for the paper "SAPE: Spatially-Adaptive Progressive Encoding for Neural Optimization".
SAPE Project page Paper Official implementation for the paper "SAPE: Spatially-Adaptive Progressive Encoding for Neural Optimization". Environment Cre
Instant neural graphics primitives: lightning fast NeRF and more
Instant Neural Graphics Primitives Ever wanted to train a NeRF model of a fox in under 5 seconds? Or fly around a scene captured from photos of a fact
Pytorch code for "DPFM: Deep Partial Functional Maps" - 3DV 2021 (Oral)
DPFM Code for "DPFM: Deep Partial Functional Maps" - 3DV 2021 (Oral) Installation This implementation runs on python = 3.7, use pip to install depend
Reimplementation of Learning Mesh-based Simulation With Graph Networks
Pytorch Implementation of Learning Mesh-based Simulation With Graph Networks This is the unofficial implementation of the approach described in the pa
Deep learning transformer model that generates unique music sequences.
music-ai Deep learning transformer model that generates unique music sequences. Abstract In 2017, a new state-of-the-art was published for natural lan
Laplace Redux -- Effortless Bayesian Deep Learning
Laplace Redux - Effortless Bayesian Deep Learning This repository contains the code to run the experiments for the paper Laplace Redux - Effortless Ba
Tackling Obstacle Tower Challenge using PPO & A2C combined with ICM.
Obstacle Tower Challenge using Deep Reinforcement Learning Unity Obstacle Tower is a challenging realistic 3D, third person perspective and procedural
Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt)
Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt) Task Training huge unsupervised deep neural networks yields to strong progress in
Implement of "Training deep neural networks via direct loss minimization" in PyTorch for 0-1 loss
This is the implementation of "Training deep neural networks via direct loss minimization" published at ICML 2016 in PyTorch. The implementation targe
Official PyTorch Implementation of "AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting".
AgentFormer This repo contains the official implementation of our paper: AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecast
Effective Use of Transformer Networks for Entity Tracking
Effective Use of Transformer Networks for Entity Tracking (EMNLP19) This is a PyTorch implementation of our EMNLP paper on the effectiveness of pre-tr
Implementation of Memory-Compressed Attention, from the paper "Generating Wikipedia By Summarizing Long Sequences"
Memory Compressed Attention Implementation of the Self-Attention layer of the proposed Memory-Compressed Attention, in Pytorch. This repository offers
An implementation of the efficient attention module.
Efficient Attention An implementation of the efficient attention module. Description Efficient attention is an attention mechanism that substantially
GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond
GCNet for Object Detection By Yue Cao, Jiarui Xu, Stephen Lin, Fangyun Wei, Han Hu. This repo is a official implementation of "GCNet: Non-local Networ
The code for Expectation-Maximization Attention Networks for Semantic Segmentation (ICCV'2019 Oral)
EMANet News The bug in loading the pretrained model is now fixed. I have updated the .pth. To use it, download it again. EMANet-101 gets 80.99 on the
Pytorch implementation of Compressive Transformers, from Deepmind
Compressive Transformer in Pytorch Pytorch implementation of Compressive Transformers, a variant of Transformer-XL with compressed memory for long-ran
Implementation of Axial attention - attending to multi-dimensional data efficiently
Axial Attention Implementation of Axial attention in Pytorch. A simple but powerful technique to attend to multi-dimensional data efficiently. It has
My take on a practical implementation of Linformer for Pytorch.
Linformer Pytorch Implementation A practical implementation of the Linformer paper. This is attention with only linear complexity in n, allowing for v
🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱
Monitor deep learning model training and hardware usage from mobile. 🔥 Features Monitor running experiments from mobile phone (or laptop) Monitor har
Official repository of "DeepMIH: Deep Invertible Network for Multiple Image Hiding", TPAMI 2022.
DeepMIH: Deep Invertible Network for Multiple Image Hiding (TPAMI 2022) This repo is the official code for DeepMIH: Deep Invertible Network for Multip
📚 A collection of all the Deep Learning Metrics that I came across which are not accuracy/loss.
📚 A collection of all the Deep Learning Metrics that I came across which are not accuracy/loss.
Node-level Graph Regression with Deep Gaussian Process Models
Node-level Graph Regression with Deep Gaussian Process Models Prerequests our implementation is mainly based on tensorflow 1.x and gpflow 1.x: python
Evolving neural network parameters in JAX.
Evolving Neural Networks in JAX This repository holds code displaying techniques for applying evolutionary network training strategies in JAX. Each sc
A basic neural network for image segmentation.
Unet_erythema_detection A basic neural network for image segmentation. 前期准备 1.在logs文件夹中下载h5权重文件,百度网盘链接在logs文件夹中 2.将所有原图 放置在“/dataset_1/JPEGImages/”文件夹
Prediction of MBA refinance Index (Mortgage prepayment)
Prediction of MBA refinance Index (Mortgage prepayment) Deep Neural Network based Model The ability to predict mortgage prepayment is of critical use
Sentiment analysis translations of the Bhagavad Gita
Sentiment and Semantic Analysis of Bhagavad Gita Translations It is well known that translations of songs and poems not only breaks rhythm and rhyming
Repository containing the PhD Thesis "Formal Verification of Deep Reinforcement Learning Agents"
Getting Started This repository contains the code used for the following publications: Probabilistic Guarantees for Safe Deep Reinforcement Learning (
FairEdit: Preserving Fairness in Graph Neural Networks through Greedy Graph Editing
FairEdit Relevent Publication FairEdit: Preserving Fairness in Graph Neural Networks through Greedy Graph Editing
Continual Learning of Long Topic Sequences in Neural Information Retrieval
ContinualPassageRanking Repository for the paper "Continual Learning of Long Topic Sequences in Neural Information Retrieval". In this repository you
Unofficial JAX implementations of Deep Learning models
JAX Models Table of Contents About The Project Getting Started Prerequisites Installation Usage Contributing License Contact About The Project The JAX
A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base Population
DeepKE is a knowledge extraction toolkit supporting low-resource and document-level scenarios for entity, relation and attribute extraction. We provide comprehensive documents, Google Colab tutorials, and online demo for beginners.
This is the official implementation of our proposed SwinMR
SwinMR This is the official implementation of our proposed SwinMR: Swin Transformer for Fast MRI Please cite: @article{huang2022swin, title={Swi
Dimension Reduced Turbulent Flow Data From Deep Vector Quantizers
Dimension Reduced Turbulent Flow Data From Deep Vector Quantizers This is an implementation of A Physics-Informed Vector Quantized Autoencoder for Dat
Optical machine for senses sensing using speckle and deep learning
# Senses-speckle [Remote Photonic Detection of Human Senses Using Secondary Speckle Patterns](https://doi.org/10.21203/rs.3.rs-724587/v1) paper Python
Similarity-based Gray-box Adversarial Attack Against Deep Face Recognition
Similarity-based Gray-box Adversarial Attack Against Deep Face Recognition Introduction Run attack: SGADV.py Objective function: foolbox/attacks/gradi
Deeplearning project at The Technological University of Denmark (DTU) about Neural ODEs for finding dynamics in ordinary differential equations and real world time series data
Authors Marcus Lenler Garsdal, [email protected] Valdemar Søgaard, [email protected] Simon Moe Sørensen, [email protected] Introduction This repo contains the
Accurate Phylogenetic Inference with Symmetry-Preserving Neural Networks
Accurate Phylogenetic Inference with a Symmetry-preserving Neural Network Model Claudia Solis-Lemus Shengwen Yang Leonardo Zepeda-Núñez This repositor
Source codes for Improved Few-Shot Visual Classification (CVPR 2020), Enhancing Few-Shot Image Classification with Unlabelled Examples
Source codes for Improved Few-Shot Visual Classification (CVPR 2020), Enhancing Few-Shot Image Classification with Unlabelled Examples (WACV 2022) and Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning (TPAMI 2022 - in submission)
Weakly Supervised Scene Text Detection using Deep Reinforcement Learning
Weakly Supervised Scene Text Detection using Deep Reinforcement Learning This repository contains the setup for all experiments performed in our Paper
This repo is the official implementation for Multi-Scale Adaptive Graph Neural Network for Multivariate Time Series Forecasting
1 MAGNN This repo is the official implementation for Multi-Scale Adaptive Graph Neural Network for Multivariate Time Series Forecasting. 1.1 The frame
Neural Koopman Lyapunov Control
Neural-Koopman-Lyapunov-Control Code for our paper: Neural Koopman Lyapunov Control Requirements dReal4: v4.19.02.1 PyTorch: 1.2.0 The learning framew
Performance Analysis of Multi-user NOMA Wireless-Powered mMTC Networks: A Stochastic Geometry Approach
Performance Analysis of Multi-user NOMA Wireless-Powered mMTC Networks: A Stochastic Geometry Approach Thanh Luan Nguyen, Tri Nhu Do, Georges Kaddoum
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Awesome production machine learning This repository contains a curated list of awesome open source libraries that will help you deploy, monitor, versi
A curated list of awesome Deep Learning tutorials, projects and communities.
Awesome Deep Learning Table of Contents Books Courses Videos and Lectures Papers Tutorials Researchers Websites Datasets Conferences Frameworks Tools
An awesome Data Science repository to learn and apply for real world problems.
AWESOME DATA SCIENCE An open source Data Science repository to learn and apply towards solving real world problems. This is a shortcut path to start s
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
applied-ml Curated papers, articles, and blogs on data science & machine learning in production. ⚙️ Figuring out how to implement your ML project? Lea
Collection of machine learning related notebooks to share.
ML_Notebooks Collection of machine learning related notebooks to share. Notebooks GAN_distributed_training.ipynb In this Notebook, TensorFlow's tutori
DeepAmandine is an artificial intelligence that allows you to talk to it for hours, you won't know the difference.
DeepAmandine This is an artificial intelligence based on GPT-3 that you can chat with, it is very nice and makes a lot of jokes. We wish you a good ex
How to detect objects in real time by using Jupyter Notebook and Neural Networks , by using Yolo3
Real Time Object Recognition From your Screen Desktop . In this post, I will explain how to build a simply program to detect objects from you desktop
LightNet++: Boosted Light-weighted Networks for Real-time Semantic Segmentation
LightNet++ !!!New Repo.!!! ⇒ EfficientNet.PyTorch: Concise, Modular, Human-friendly PyTorch implementation of EfficientNet with Pre-trained Weights !!
Reference implementation for Structured Prediction with Deep Value Networks
Deep Value Network (DVN) This code is a python reference implementation of DVNs introduced in Deep Value Networks Learn to Evaluate and Iteratively Re
Deep Watershed Transform for Instance Segmentation
Deep Watershed Transform Performs instance level segmentation detailed in the following paper: Min Bai and Raquel Urtasun, Deep Watershed Transformati
FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics
FusionNet_Pytorch FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics Requirements Pytorch 0.1.11 Pyt
Code for "Salient Deconvolutional Networks, Aravindh Mahendran, Andrea Vedaldi, ECCV 2016"
deconvnet_analysis Code for "Salient Deconvolutional Networks, Aravindh Mahendran, Andrea Vedaldi, ECCV 2016" Parts of this code Generate figures in t
TransferNet: Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network
TransferNet: Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network Created by Seunghoon Hong, Junhyuk Oh,
A simple python module to generate anchor (aka default/prior) boxes for object detection tasks.
PyBx WIP A simple python module to generate anchor (aka default/prior) boxes for object detection tasks. Calculated anchor boxes are returned as ndarr
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
Generic Foreground Segmentation in Images
Pixel Objectness The following repository contains pretrained model for pixel objectness. Please visit our project page for the paper and visual resul
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
Deep Learning for Human Part Discovery in Images - Chainer implementation
Deep Learning for Human Part Discovery in Images - Chainer implementation NOTE: This is not official implementation. Original paper is Deep Learning f
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
MOOSE (Multi-organ objective segmentation) a data-centric AI solution that generates multilabel organ segmentations to facilitate systemic TB whole-person research
MOOSE (Multi-organ objective segmentation) a data-centric AI solution that generates multilabel organ segmentations to facilitate systemic TB whole-person research.The pipeline is based on nn-UNet and has the capability to segment 120 unique tissue classes from a whole-body 18F-FDG PET/CT image.
auto_code_complete is a auto word-completetion program which allows you to customize it on your need
auto_code_complete v1.3 purpose and usage auto_code_complete is a auto word-completetion program which allows you to customize it on your needs. the m
Deep Ensemble Learning with Jet-Like architecture
Ransomware analysis using DEL with jet-like architecture comprising two CNN wings, a sparse AE tail, a non-linear PCA to produce a diverse feature space, and an MLP nose
Eff video representation - Efficient video representation through neural fields
Neural Residual Flow Fields for Efficient Video Representations 1. Download MPI
Cryptocurrency Prediction with Artificial Intelligence (Deep Learning via LSTM Neural Networks)
Cryptocurrency Prediction with Artificial Intelligence (Deep Learning via LSTM Neural Networks)- Emirhan BULUT
Stock-Prediction - prediction of stock market movements using sentiment analysis and deep learning.
Stock-Prediction- In this project, we aim to enhance the prediction of stock market movements using sentiment analysis and deep learning. We divide th
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
The code succinctly shows how our ensemble learning based on deep learning CNN is used for LAM-avulsion-diagnosis.
deep-learning-LAM-avulsion-diagnosis The code succinctly shows how our ensemble learning based on deep learning CNN is used for LAM-avulsion-diagnosis
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
Training a Resilient Q-Network against Observational Interference, Causal Inference Q-Networks
Obs-Causal-Q-Network AAAI 2022 - Training a Resilient Q-Network against Observational Interference Preprint | Slides | Colab Demo | Environment Setup
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.
Deep motion generator collections
GenMotion GenMotion (/gen’motion/) is a Python library for making skeletal animations. It enables easy dataset loading and experiment sharing for synt
Generative Autoregressive, Normalized Flows, VAEs, Score-based models (GANVAS)
GANVAS-models This is an implementation of various generative models. It contains implementations of the following: Autoregressive Models: PixelCNN, G
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
Keras code and weights files for popular deep learning models.
Trained image classification models for Keras THIS REPOSITORY IS DEPRECATED. USE THE MODULE keras.applications INSTEAD. Pull requests will not be revi
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
This is code of book "Learn Deep Learning with PyTorch"
深度学习入门之PyTorch Learn Deep Learning with PyTorch 非常感谢您能够购买此书,这个github repository包含有深度学习入门之PyTorch的实例代码。由于本人水平有限,在写此书的时候参考了一些网上的资料,在这里对他们表示敬意。由于深度学习的技术在
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
A set of Deep Reinforcement Learning Agents implemented in Tensorflow.
Deep Reinforcement Learning Agents This repository contains a collection of reinforcement learning algorithms written in Tensorflow. The ipython noteb
Jupyter notebooks for using & learning Keras
deep-learning-with-keras-notebooks 這個github的repository主要是個人在學習Keras的一些記錄及練習。希望在學習過程中發現到一些好的資訊與範例也可以對想要學習使用 Keras來解決問題的同好,或是對深度學習有興趣的在學學生可以有一些方便理解與上手範例
Scenarios, tutorials and demos for Autonomous Driving
The Autonomous Driving Cookbook (Preview) NOTE: This project is developed and being maintained by Project Road Runner at Microsoft Garage. This is cur
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.
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
Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).
Knowledge Informed Machine Learning using a Weibull-based Loss Function Exploring the concept of knowledge-informed machine learning with the use of a
Pytorch implementation of local motion and contrast prior driven deep network (MoCoPnet)
MoCoPnet: Exploring Local Motion and Contrast Priors for Infrared Small Target Super-Resolution Pytorch implementation of local motion and contrast pr