Python Deep-gaussian-processes Resources

Learning to Prompt for Continual Learning (L2P) Official Jax Implementation L2P is a novel continual learning technique which learns to dynamically pr

DI-treetensor treetensor is a generalized tree-based tensor structure mainly developed by OpenDILab Contributors. Almost all the operation can be supp

FSL-Mate is a collection of resources for few-shot learning (FSL). In particular, FSL-Mate currently contains FewShotPapers: a paper list which tracks

GalaXC GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification @InProceedings{Saini21, author = {Saini, D. and Jain,

Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning. Circuit Training is an open-s

PL-LOW A high-performance deep learning model lightweight pipeline that gradually lightens deep neural networks in order to utilize high-performance d

Learn Machine Learning Algorithms by doing projects in Python and R Programming Language. This repo covers all aspect of Machine Learning Algorithms.

DeepFaceLive - Live Deep Fake in python, Real-time face swap for PC streaming or video calls

Deep_Learning & Neural_Network_Lab 实验环境 Python 3.9 Anaconda3(官网下载或清华镜像都行) PyTorch 1.10.1(安装代码如下) conda install pytorch torchvision torchaudio cudatool

Can We Find Neurons that Cause Unrealistic Images in Deep Generative Networks? Artifact Detection/Correction - Offcial PyTorch Implementation This rep

QPT - Quick packaging tool 快捷封装工具 GitHub主页 | Gitee主页 QPT是一款可以“模拟”开发环境的多功能封装工具，最短只需一行命令即可将普通的Python脚本打包成EXE可执行程序，并选择性添加CUDA和NoAVX的支持，尽可能兼容更多的用户环境。 感觉还可

This is the repository for The Machine Learning Workshops, published by AI DOJO. It contains all the workshop's code with supporting project files necessary to work through the code.

Applying BERT Fine Tuning to Sentiment Classification on Amazon Reviews Abstract Sentiment analysis has made great progress in recent years, due to th

Brain-Tumor-Detection A convolutional neural network model built with Tensorflow & Keras to detect brain tumor and its different variants. Data of the

Synapse Machine Learning SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. Sy

this is a simple artificial neural network model using deep learning and torch-audio to classify cats and dog sounds.

ParaGen is a PyTorch deep learning framework for parallel sequence generation. Apart from sequence generation, ParaGen also enhances various NLP tasks, including sequence-level classification, extraction and generation.

PyGRANSO PyGRANSO: A PyTorch-enabled port of GRANSO with auto-differentiation Please check https://ncvx.org/PyGRANSO for detailed instructions (introd

nixtlats:Deep Learning for Time Series Forecasting [nikstla] (noun, nahuatl) Period of time. State-of-the-art time series forecasting for pytorch. Nix

Predicting-Clothing-Types Predicting 10 different clothing types using Xception pre-trained model from Keras library. It is reimplemented version from

Hello, This Notebook Contains Example of Corona Virus Tweets Multi Class Classification. - Classes is: Extremely Positive, Positive, Extremely Negativ

Deep Causal Reasoning for Recommender Systems The codes are associated with the following paper: Deep Causal Reasoning for Recommendations, Yaochen Zh

FGVC8 Exploring Vision Transformers for Fine-grained Classification paper presented at the CVPR 2021, The Eight Workshop on Fine-Grained Visual Catego

RETRO - Pytorch (wip) Implementation of RETRO, Deepmind's Retrieval based Attent

DPFM Code for "DPFM: Deep Partial Functional Maps" - 3DV 2021 (Oral) Installation This implementation runs on python = 3.7, use pip to install depend

Pytorch Implementation of Learning Mesh-based Simulation With Graph Networks This is the unofficial implementation of the approach described in the pa

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 This repository contains the code to run the experiments for the paper Laplace Redux - Effortless Ba

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) Task Training huge unsupervised deep neural networks yields to strong progress in

This is the implementation of "Training deep neural networks via direct loss minimization" published at ICML 2016 in PyTorch. The implementation targe

AgentFormer This repo contains the official implementation of our paper: AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecast

Memory Compressed Attention Implementation of the Self-Attention layer of the proposed Memory-Compressed Attention, in Pytorch. This repository offers

Efficient Attention An implementation of the efficient attention module. Description Efficient attention is an attention mechanism that substantially

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

Compressive Transformer in Pytorch Pytorch implementation of Compressive Transformers, a variant of Transformer-XL with compressed memory for long-ran

Axial Attention Implementation of Axial attention in Pytorch. A simple but powerful technique to attend to multi-dimensional data efficiently. It has

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 mobile. 🔥 Features Monitor running experiments from mobile phone (or laptop) Monitor har

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.

Node-level Graph Regression with Deep Gaussian Process Models Prerequests our implementation is mainly based on tensorflow 1.x and gpflow 1.x: python

Prediction of MBA refinance Index (Mortgage prepayment) Deep Neural Network based Model The ability to predict mortgage prepayment is of critical use

Sentiment and Semantic Analysis of Bhagavad Gita Translations It is well known that translations of songs and poems not only breaks rhythm and rhyming

Getting Started This repository contains the code used for the following publications: Probabilistic Guarantees for Safe Deep Reinforcement Learning (

JAX Models Table of Contents About The Project Getting Started Prerequisites Installation Usage Contributing License Contact About The Project The JAX

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.

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 This is an implementation of A Physics-Informed Vector Quantized Autoencoder for Dat

# 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 Introduction Run attack: SGADV.py Objective function: foolbox/attacks/gradi

A Python package for simulating Active Inference agents in Markov Decision Process environments. Please see our companion preprint on arxiv for an ove

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 This repository contains the setup for all experiments performed in our Paper

Awesome production machine learning This repository contains a curated list of awesome open source libraries that will help you deploy, monitor, versi

Awesome Deep Learning Table of Contents Books Courses Videos and Lectures Papers Tutorials Researchers Websites Datasets Conferences Frameworks Tools

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

applied-ml Curated papers, articles, and blogs on data science & machine learning in production. ⚙️ Figuring out how to implement your ML project? Lea

ML_Notebooks Collection of machine learning related notebooks to share. Notebooks GAN_distributed_training.ipynb In this Notebook, TensorFlow's tutori

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 Performs instance level segmentation detailed in the following paper: Min Bai and Raquel Urtasun, Deep Watershed Transformati

FusionNet_Pytorch FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics Requirements Pytorch 0.1.11 Pyt

TransferNet: Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network Created by Seunghoon Hong, Junhyuk Oh,

PyBx WIP A simple python module to generate anchor (aka default/prior) boxes for object detection tasks. Calculated anchor boxes are returned as ndarr

Neural-Network-Basics Aim of this Repository: From Perceptron model to Deep Neural Network (from scratch) in Python. ** Currently working on a basic N

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 This repo contains a TensorFlow implementation of weakly supervised instance segmentation as described

Deep Learning for Human Part Discovery in Images - Chainer implementation NOTE: This is not official implementation. Original paper is Deep Learning f

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 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.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 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

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

Cryptocurrency Prediction with Artificial Intelligence (Deep Learning via LSTM Neural Networks)- Emirhan BULUT

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 which will then be used to generate residuals

Simple implementation of Equivariant GNN A short implementation of E(n) Equivariant Graph Neural Networks for HOMO energy prediction. Just 50 lines of

deep learning model, heat map, data prepo

deep-learning-LAM-avulsion-diagnosis The code succinctly shows how our ensemble learning based on deep learning CNN is used for LAM-avulsion-diagnosis

Obs-Causal-Q-Network AAAI 2022 - Training a Resilient Q-Network against Observational Interference Preprint | Slides | Colab Demo | Environment Setup

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.

GenMotion GenMotion (/gen’motion/) is a Python library for making skeletal animations. It enables easy dataset loading and experiment sharing for synt

GANVAS-models This is an implementation of various generative models. It contains implementations of the following: Autoregressive Models: PixelCNN, G

Designed a greedy algorithm based on Markov sequential decision-making process in MATLAB/Python to optimize using Gurobi solver, the wheel size, gear shifting sequence by modeling drivetrain constraints to achieve maximum laps in a race with a 2-hour time window.

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

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

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 This repo provides a clean implementation of YoloV3 in TensorFlow 2.0 using all the best practices. Key Features

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) Dr. Tirthajyoti Sarkar, Fremont, California (Please feel free to connect on LinkedIn here) Also

Deep Reinforcement Learning Agents This repository contains a collection of reinforcement learning algorithms written in Tensorflow. The ipython noteb

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

The Autonomous Driving Cookbook (Preview) NOTE: This project is developed and being maintained by Project Road Runner at Microsoft Garage. This is cur

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.

Knowledge Informed Machine Learning using a Weibull-based Loss Function Exploring the concept of knowledge-informed machine learning with the use of a

MoCoPnet: Exploring Local Motion and Contrast Priors for Infrared Small Target Super-Resolution Pytorch implementation of local motion and contrast pr

This repository is no longer maintained. Please use our new Softlearning package instead. Soft Actor-Critic Soft actor-critic is a deep reinforcement

Info This is the code repository of the work Tackling the Class Imbalance Problem of Deep Learning Based Head and Neck Organ Segmentation from Elias T

MothPruning Scientific Overview Originally inspired by biological nervous systems, deep neural networks (DNNs) are powerful computational tools for mo

AAF framework Framework generalities This repository contains the code of the AAF framework proposed in this paper. The main idea behind this work is