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Muriqui Optimizer - A convex mixed integer nonlinear programming solver
PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning https://arxiv.org/abs/1611.09940
in progress
[Re] Exact Combinatorial Optimization with Graph Convolutional Neural Networks
A course on Optimization Methods
A notebook tutorial series for performing predictive maintenance using machine learning
Example of Multiple Multivariate Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras.
PyTorch implementation of DGCNN
ipython notebooks from quantopian lectures series
Using reinforcement learning to solve integer programming. The environment is created by teaching staff of E4575 Spring 2021, led by Professor Shipra Agrawal.
Repository to store files pertaining to Reinforcement Learning project which aims to solve integer programming problems by learning to choose an optimal cut from a get of gomory cuts.
Learning to branch with reinforcement learning using retrospective trajectories for exact combinatorial optimisation.
simple customizable risk scores in python
A reinforcement learning approach to choosing Gomory cuts for integer programming.
This repository stores the implementation of an Reinforcement Learning-based parameter controller for evolutionary and swarm-based algorithms.
Reinforcement Learning in PyTorch
Repository containing supplementary data and code for "A Robust Approach to Chance Constrained Optimal Power Flow with Renewable Generation" by Lubin, Dvorkin, and Backhaus
Code for machine learning workshop given to Sanger Systems group
A simple implementation of the Benders decomposition method with JuMP
Multivariate Time Series Forecasting with efficient Transformers. Code for the paper "Long-Range Transformers for Dynamic Spatiotemporal Forecasting."
A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
Traffic Assignment frameworK (TAsK). Traffic assignment algorithms for the conventional and non-additive traffic assignment problems.
This paper have been presented in the form of an oral presentation at the IJCNN-2019 conference. The title is "Transformation-gated LSTM: efficient capture of short-term mutation dependencies for multivariate time series prediction tasks".
Sensor data of a renowned power plant has given by a reliable source to forecast some feature. Initially the work has done with KNIME software. Now the goal is to do the prediction/forecasting with machine learning. The idea is to check the result of forecast with univariate and multivariate time series data. Regression method, Statistical method.
Temporal Pattern Attention for Multivariate Time Series Forecasting
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.