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This repository contains code for different implementations of assorted reinforcement learning algorithms (evolutionary ones as well). My aim is to create a place where algorithms can be explored and manipulated easily, and implemented on interesting environments.
My matlab homework files
Google Android官方培训课程中文版
AOP in PHP
Web interface for browsing, search and filtering recent arxiv submissions
An experimental open-source attempt to make GPT-4 fully autonomous.
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
This is the code for "Capsule Networks: An Improvement to Convolutional Networks" by Siraj Raval on Youtube
I took Andrew Ng's Machine Learning course on Coursera and did the homework assigments... but, on my own in python because I love jupyter notebooks!
Age-structured SEIR model for COVID-19 outbreak in Wuhan, China
My Solutions of Assignments of CS234: Reinforcement Learning Winter 2019
Differentiable convex optimization layers
code for performing active flow control of the 2D Karman street using Deep Reinforcement Learning
Robust active flow control over a range of Reynolds numbers using artificial neural network trained through deep reinforcement learning
Computational analysis of optimal patterns of current injection for deep brain stimulation
Books for machine learning, deep learning, math, NLP, CV, RL, etc. 一些机器学习、深度学习等相关话题的书籍。
Collection of Deep Reinforcement Learning Algorithms implemented in PyTorch.
Hands-on Deep Reinforcement Learning, published by Packt
My Exploration on Deep Reinforcement Learning Survey
PyTorch implementations of Deep Reinforcement Learning algorithms (DQN, DDQN, A2C, VPG, TRPO, PPO, DDPG, TD3, SAC, SAC-AEA)
neural networks to learn Koopman eigenfunctions
Matlab code to compute traveling wave solutions to Euler for a density stratified with linear shear as well as compute the spectral stability of the traveling wave solutions. Uses a modification of the nonlocal fomulation of the water-wave problem due to Ablowitz, Fokas, and Musslimani.
In this paper, we will be evaluating numerical methods for direct and iterative solvers of linear systems. From class we have discussed the various methods; Gauss elimination with pivoting techniques, Jacobi Iterative Method, Gauss-Seidel Iterative Method, Successive Over-Relaxation Method, Iterative Refinement Method, and Conjugate Gradient Method. In this paper, using Python programming language, we will discuss how each method evaluates various linear systems of equations, and then we will discuss the complexity, accuracy, and stability of each method
Code for DragGAN (SIGGRAPH 2023)
Methods that find the largest and smallest eigenvalue to a nxn matrix.
A simple GUI for running goagent under mac
Example demonstrating how gradient descent may be used to solve a linear regression problem
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.