5993 Repositories
Python multi-domain-learning Libraries
TTS is a library for advanced Text-to-Speech generation.
TTS is a library for advanced Text-to-Speech generation. It's built on the latest research, was designed to achieve the best trade-off among ease-of-training, speed and quality. TTS comes with pretrained models, tools for measuring dataset quality and already used in 20+ languages for products and research projects.
SLIDE : In Defense of Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning Systems
The SLIDE package contains the source code for reproducing the main experiments in this paper. Dataset The Datasets can be downloaded in Amazon-
Proto-RL: Reinforcement Learning with Prototypical Representations
Proto-RL: Reinforcement Learning with Prototypical Representations This is a PyTorch implementation of Proto-RL from Reinforcement Learning with Proto
Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch
Cross Transformers - Pytorch (wip) Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch Install $ pip install cross-t
PClean: A Domain-Specific Probabilistic Programming Language for Bayesian Data Cleaning
PClean: A Domain-Specific Probabilistic Programming Language for Bayesian Data Cleaning Warning: This is a rapidly evolving research prototype.
DLFlow is a deep learning framework.
DLFlow是一套深度学习pipeline,它结合了Spark的大规模特征处理能力和Tensorflow模型构建能力。利用DLFlow可以快速处理原始特征、训练模型并进行大规模分布式预测,十分适合离线环境下的生产任务。利用DLFlow,用户只需专注于模型开发,而无需关心原始特征处理、pipeline构建、生产部署等工作。
Official PyTorch implementation of Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations
Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations Zhenyu Jiang, Yifeng Zhu, Maxwell Svetlik, Kuan Fang, Yu
Domain Connectivity Analysis Tools to analyze aggregate connectivity patterns across a set of domains during security investigations
DomainCAT (Domain Connectivity Analysis Tool) Domain Connectivity Analysis Tool is used to analyze aggregate connectivity patterns across a set of dom
Multi-Scale Aligned Distillation for Low-Resolution Detection (CVPR2021)
MSAD Multi-Scale Aligned Distillation for Low-Resolution Detection Lu Qi*, Jason Kuen*, Jiuxiang Gu, Zhe Lin, Yi Wang, Yukang Chen, Yanwei Li, Jiaya J
Quantum Machine Learning
The Machine Learning package simply contains sample datasets at present. It has some classification algorithms such as QSVM and VQC (Variational Quantum Classifier), where this data can be used for experiments, and there is also QGAN (Quantum Generative Adversarial Network) algorithm.
Newt - a Gaussian process library in JAX.
Newt __ \/_ (' \`\ _\, \ \\/ /`\/\ \\ \ \\
PyTorch reimplementation of the paper Involution: Inverting the Inherence of Convolution for Visual Recognition [CVPR 2021].
Involution: Inverting the Inherence of Convolution for Visual Recognition Unofficial PyTorch reimplementation of the paper Involution: Inverting the I
Elliot is a comprehensive recommendation framework that analyzes the recommendation problem from the researcher's perspective.
Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
POT : Python Optimal Transport
This open source Python library provide several solvers for optimization problems related to Optimal Transport for signal, image processing and machine learning.
Object Detection and Multi-Object Tracking
Object Detection and Multi-Object Tracking
Using deep actor-critic model to learn best strategies in pair trading
Deep-Reinforcement-Learning-in-Stock-Trading Using deep actor-critic model to learn best strategies in pair trading Abstract Partially observed Markov
Deep Reinforcement Learning based Trading Agent for Bitcoin
Deep Trading Agent Deep Reinforcement Learning based Trading Agent for Bitcoin using DeepSense Network for Q function approximation. For complete deta
Reinforcement Learning for finance
Reinforcement Learning for Finance We apply reinforcement learning for stock trading. Fetch Data Example import utils # fetch symbols from yahoo fina
Reinforcement Learning for Automated Trading
Reinforcement Learning for Automated Trading This thesis has been realized for the obtention of the Master's in Mathematical Engineering at the Polite
PGPortfolio: Policy Gradient Portfolio, the source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"(https://arxiv.org/pdf/1706.10059.pdf).
This is the original implementation of our paper, A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem (arXiv:1706.1
:boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling
bulbea "Deep Learning based Python Library for Stock Market Prediction and Modelling." Table of Contents Installation Usage Documentation Dependencies
Learning to trade under the reinforcement learning framework
Trading Using Q-Learning In this project, I will present an adaptive learning model to trade a single stock under the reinforcement learning framework
Algorithmic trading with deep learning experiments
Deep-Trading Algorithmic trading with deep learning experiments. Now released part one - simple time series forecasting. I plan to implement more soph
This project uses reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can learn to read tape. The project is dedicated to hero in life great Jesse Livermore.
Reinforcement-trading This project uses Reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can
A resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of algorithmic trading
A tour through tensorflow with financial data I present several models ranging in complexity from simple regression to LSTM and policy networks. The s
This project provides a stock market environment using OpenGym with Deep Q-learning and Policy Gradient.
Stock Trading Market OpenAI Gym Environment with Deep Reinforcement Learning using Keras Overview This project provides a general environment for stoc
Predict stock movement with Machine Learning and Deep Learning algorithms
Project Overview Stock market movement prediction using LSTM Deep Neural Networks and machine learning algorithms Software and Library Requirements Th
Reinforcement Learning for Portfolio Management
qtrader Reinforcement Learning for Portfolio Management Why Reinforcement Learning? Learns the optimal action, rather than models the market. Adaptive
Technical experimentations to beat the stock market using deep learning :chart_with_upwards_trend:
DeepStock Technical experimentations to beat the stock market using deep learning. Experimentations Deep Learning Stock Prediction with Daily News Hea
Use deep learning, genetic programming and other methods to predict stock and market movements
StockPredictions Use classic tricks, neural networks, deep learning, genetic programming and other methods to predict stock and market movements. Both
High frequency AI based algorithmic trading module.
Flow Flow is a high frequency algorithmic trading module that uses machine learning to self regulate and self optimize for maximum return. The current
Algorithmic trading using machine learning.
Algorithmic Trading This machine learning algorithm was built using Python 3 and scikit-learn with a Decision Tree Classifier. The program gathers sto
OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network
Stock Price Prediction of Apple Inc. Using Recurrent Neural Network OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network Dataset:
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
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
Modeling High-Frequency Limit Order Book Dynamics Using Machine Learning Framework to capture the dynamics of high-frequency limit order books. Overvi
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
Using python and scikit-learn to make stock predictions
MachineLearningStocks in python: a starter project and guide EDIT as of Feb 2021: MachineLearningStocks is no longer actively maintained MachineLearni
Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]
Advances in Financial Machine Learning Exercises Experimental solutions to selected exercises from the book Advances in Financial Machine Learning by
Trading environnement for RL agents, backtesting and training.
TradzQAI Trading environnement for RL agents, backtesting and training. Live session with coinbasepro-python is finaly arrived ! Available sessions: L
Scalable, event-driven, deep-learning-friendly backtesting library
...Minimizing the mean square error on future experience. - Richard S. Sutton BTGym Scalable event-driven RL-friendly backtesting library. Build on
Trading Gym is an open source project for the development of reinforcement learning algorithms in the context of trading.
Trading Gym Trading Gym is an open-source project for the development of reinforcement learning algorithms in the context of trading. It is currently
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.
TradingGym TradingGym is a toolkit for training and backtesting the reinforcement learning algorithms. This was inspired by OpenAI Gym and imitated th
FireDM is a python open source (Internet Download Manager) with multi-connections, high speed engine, it downloads general files and videos from youtube and tons of other streaming websites .
python open source (Internet Download Manager) with multi-connections, high speed engine, based on python, LibCurl, and youtube_dl https://github.com/firedm/FireDM
Processing and interpolating spatial data with a twist of machine learning
Documentation | Documentation (dev version) | Contact | Part of the Fatiando a Terra project About Verde is a Python library for processing spatial da
Net2Vis automatically generates abstract visualizations for convolutional neural networks from Keras code.
Automatic neural network visualizations generated in your browser!
PyTorch implementation of Algorithm 1 of "On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models"
Code for On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models This repository will reproduce the main results from our pape
PyTorch implementation of the Deep SLDA method from our CVPRW-2020 paper "Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis"
Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis This is a PyTorch implementation of the Deep Streaming Linear Discriminant
《LightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text Classification》(AAAI 2021) GitHub:
LightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text Classification
Demo code for paper "Learning optical flow from still images", CVPR 2021.
Depthstillation Demo code for "Learning optical flow from still images", CVPR 2021. [Project page] - [Paper] - [Supplementary] This code is provided t
Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)
Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)
100 Days of Machine and Deep Learning Code
💯 Days of Machine Learning and Deep Learning Code MACHINE LEARNING TOPICS COVERED - FROM SCRATCH Linear Regression Logistic Regression K Means Cluste
Learning to Estimate Hidden Motions with Global Motion Aggregation
Learning to Estimate Hidden Motions with Global Motion Aggregation (GMA) This repository contains the source code for our paper: Learning to Estimate
Model-based reinforcement learning in TensorFlow
Bellman Website | Twitter | Documentation (latest) What does Bellman do? Bellman is a package for model-based reinforcement learning (MBRL) in Python,
PyTorch code for the paper "Curriculum Graph Co-Teaching for Multi-target Domain Adaptation" (CVPR2021)
PyTorch code for the paper "Curriculum Graph Co-Teaching for Multi-target Domain Adaptation" (CVPR2021) This repo presents PyTorch implementation of M
Neural Reprojection Error: Merging Feature Learning and Camera Pose Estimation
Neural Reprojection Error: Merging Feature Learning and Camera Pose Estimation This is the official repository for our paper Neural Reprojection Error
Learning recognition/segmentation models without end-to-end training. 40%-60% less GPU memory footprint. Same training time. Better performance.
InfoPro-Pytorch The Information Propagation algorithm for training deep networks with local supervision. (ICLR 2021) Revisiting Locally Supervised Lea
Layout Parser is a deep learning based tool for document image layout analysis tasks.
A Python Library for Document Layout Understanding
Oppia is an online learning tool that enables anyone to easily create and share interactive activities
Oppia is an online learning tool that enables anyone to easily create and share interactive activities (called 'explorations'). These activities simulate a one-on-one conversation with a tutor, making it possible for students to learn by doing while getting feedback.
Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution
FAU Implementation of the paper: Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution. Yingruo
Planar Prior Assisted PatchMatch Multi-View Stereo
ACMP [News] The code for ACMH is released!!! [News] The code for ACMM is released!!! About This repository contains the code for the paper Planar Prio
[AAAI 2021] MVFNet: Multi-View Fusion Network for Efficient Video Recognition
MVFNet: Multi-View Fusion Network for Efficient Video Recognition (AAAI 2021) Overview We release the code of the MVFNet (Multi-View Fusion Network).
[WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs
New Benchmarks for Learning on Non-Homophilous Graphs Here are the codes and datasets accompanying the paper: New Benchmarks for Learning on Non-Homop
Official PyTorch implementation of MX-Font (Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Experts)
Introduction Pytorch implementation of Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Expert. | paper Song Park1
A django integration for huey task queue that supports multi queue management
django-huey This package is an extension of huey contrib djhuey package that allows users to manage multiple queues. Installation Using pip package ma
Hands-on machine learning workshop
emb-ntua-workshop This workshop discusses introductory concepts of machine learning and data mining following a hands-on approach using popular tools
Polyglot Machine Learning example for scraping similar news articles.
Polyglot Machine Learning example for scraping similar news articles In this example, we will see how we can work with Machine Learning applications w
Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GanFormer and TransGan paper
TransGanFormer (wip) Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GansFormer and TransGan paper. I
Rethinking the Importance of Implementation Tricks in Multi-Agent Reinforcement Learning
MARL Tricks Our codes for RIIT: Rethinking the Importance of Implementation Tricks in Multi-AgentReinforcement Learning. We implemented and standardiz
CoReNet is a technique for joint multi-object 3D reconstruction from a single RGB image.
CoReNet CoReNet is a technique for joint multi-object 3D reconstruction from a single RGB image. It produces coherent reconstructions, where all objec
The source code for the Cutoff data augmentation approach proposed in this paper: "A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation".
Cutoff: A Simple Data Augmentation Approach for Natural Language This repository contains source code necessary to reproduce the results presented in
AOT-GAN for High-Resolution Image Inpainting (codebase for image inpainting)
AOT-GAN for High-Resolution Image Inpainting Arxiv Paper | AOT-GAN: Aggregated Contextual Transformations for High-Resolution Image Inpainting Yanhong
Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT
CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT CheXbert is an accurate, automated dee
Official implementation for NIPS'17 paper: PredRNN: Recurrent Neural Networks for Predictive Learning Using Spatiotemporal LSTMs.
PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning The predictive learning of spatiotemporal sequences aims to generate future
PyTorch implementation for COMPLETER: Incomplete Multi-view Clustering via Contrastive Prediction (CVPR 2021)
Completer: Incomplete Multi-view Clustering via Contrastive Prediction This repo contains the code and data of the following paper accepted by CVPR 20
A Collection of Conference & School Notes in Machine Learning 🦄📝🎉
Machine Learning Conference & Summer School Notes. 🦄📝🎉
Adversarial Adaptation with Distillation for BERT Unsupervised Domain Adaptation
Knowledge Distillation for BERT Unsupervised Domain Adaptation Official PyTorch implementation | Paper Abstract A pre-trained language model, BERT, ha
Semi-supervised Learning for Sentiment Analysis
Neural-Semi-supervised-Learning-for-Text-Classification-Under-Large-Scale-Pretraining Code, models and Datasets for《Neural Semi-supervised Learning fo
The implementation of ICASSP 2020 paper "Pixel-level self-paced learning for super-resolution"
Pixel-level Self-Paced Learning for Super-Resolution This is an official implementaion of the paper Pixel-level Self-Paced Learning for Super-Resoluti
Block-wisely Supervised Neural Architecture Search with Knowledge Distillation (CVPR 2020)
DNA This repository provides the code of our paper: Blockwisely Supervised Neural Architecture Search with Knowledge Distillation. Illustration of DNA
(ImageNet pretrained models) The official pytorch implemention of the TPAMI paper "Res2Net: A New Multi-scale Backbone Architecture"
Res2Net The official pytorch implemention of the paper "Res2Net: A New Multi-scale Backbone Architecture" Our paper is accepted by IEEE Transactions o
Codes for NAACL 2021 Paper "Unsupervised Multi-hop Question Answering by Question Generation"
Unsupervised-Multi-hop-QA This repository contains code and models for the paper: Unsupervised Multi-hop Question Answering by Question Generation (NA
《Improving Unsupervised Image Clustering With Robust Learning》(2020)
Improving Unsupervised Image Clustering With Robust Learning This repo is the PyTorch codes for "Improving Unsupervised Image Clustering With Robust L
A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)
A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)
Picasso: A CUDA-based Library for Deep Learning over 3D Meshes
The Picasso Library is intended for complex real-world applications with large-scale surfaces, while it also performs impressively on the small-scale applications over synthetic shape manifolds. We have upgraded the point cloud modules of SPH3D-GCN from homogeneous to heterogeneous representations, and included the upgraded modules into this latest work as well. We are happy to announce that the work is accepted to IEEE CVPR2021.
Personalized Federated Learning using Pytorch (pFedMe)
Personalized Federated Learning with Moreau Envelopes (NeurIPS 2020) This repository implements all experiments in the paper Personalized Federated Le
《LXMERT: Learning Cross-Modality Encoder Representations from Transformers》(EMNLP 2020)
The Most Important Thing. Our code is developed based on: LXMERT: Learning Cross-Modality Encoder Representations from Transformers
Code to reproduce the experiments in the paper "Transformer Based Multi-Source Domain Adaptation" (EMNLP 2020)
Transformer Based Multi-Source Domain Adaptation Dustin Wright and Isabelle Augenstein To appear in EMNLP 2020. Read the preprint: https://arxiv.org/a
Official implementation of "Dynamic Anchor Learning for Arbitrary-Oriented Object Detection" (AAAI2021).
DAL This project hosts the official implementation for our AAAI 2021 paper: Dynamic Anchor Learning for Arbitrary-Oriented Object Detection [arxiv] [c
UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning
UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning This is the official PyTorch implementation for UniMoCo pape
Code release for "Transferable Semantic Augmentation for Domain Adaptation" (CVPR 2021)
Transferable Semantic Augmentation for Domain Adaptation Code release for "Transferable Semantic Augmentation for Domain Adaptation" (CVPR 2021) Paper
Examples and code for the Practical Machine Learning workshop series
Practical Machine Learning Workshop Series Practical Machine Learning for Quantitative Finance Post conference workshop at the WBS Spring Conference D
One destination for all the developer's learning resources.
DevResources One destination for all the developer's learning resources. Find all of your learning resources under one roof and add your own. Live ✨ Y
Code for CVPR 2021 paper: Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning
Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning This is the PyTorch companion code for the paper: A
Learning Dense Representations of Phrases at Scale (Lee et al., 2020)
DensePhrases DensePhrases provides answers to your natural language questions from the entire Wikipedia in real-time. While it efficiently searches th
The code release of paper 'Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization' NIPS 2020.
Domain Generalization for Medical Imaging Classification with Linear Dependency Regularization The code release of paper 'Domain Generalization for Me
Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation
SimplePose Code and pre-trained models for our paper, “Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation”, a
Learning Spatio-Temporal Transformer for Visual Tracking
STARK The official implementation of the paper Learning Spatio-Temporal Transformer for Visual Tracking Hiring research interns for visual transformer
Library of various Few-Shot Learning frameworks for text classification
FewShotText This repository contains code for the paper A Neural Few-Shot Text Classification Reality Check Environment setup # Create environment pyt
Implementation of the paper "Language-agnostic representation learning of source code from structure and context".
Code Transformer This is an official PyTorch implementation of the CodeTransformer model proposed in: D. Zügner, T. Kirschstein, M. Catasta, J. Leskov
The guide to tackle with the Text Summarization
The guide to tackle with the Text Summarization