Maximum Entropy Model and Expectation-maximization algorithm 最大熵模型与EM算法

Expectation-Maximization (EM) algorithm in Matlab

Incorporating Transformer and LSTM to Kalman Filter with EM algorithm

Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random g…

Robot obstacle avoidance with reinforcement learning

Final project for "Control systems for robotics" - simulation of obstacle avoidance on an autonomous car using MPC

Design a control system on Matlab for robots so that they are able to form a defined shape, then Artificial Potential Field method is applied for robots to avoid obstacles

离线版本的电子书《LeetCode Cookbook》PDF https://github.com/halfrost/LeetCode-Go/releases/

战五渣学习日志记录

A GPT-4 AI Tutor Prompt for customizable personalized learning experiences.

Efficient Deep Learning Systems course materials (HSE, YSDA)

FinRL: Financial Reinforcement Learning. 🔥

PyTorch implementations of deep reinforcement learning algorithms and environments

Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch

Python Implementation of Reinforcement Learning: An Introduction

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

Intro to Reinforcement Learning (强化学习纲要）

Chinese Translation for Book 《Reinforcement Learning- An Introduction》-Second Edition

Notes and exercise solutions for second edition of Sutton & Barto's book

This is the coded used in my master's thesis to simulate an iterative stochastic model that is used to approximate network dynamics as a stochastic mean field.

Implement 2D Ising model using mean field theory, Onsager's formula and Monte Carlo simulation. Course project of Thermodynamics and Statistical Mechanics.

A framework for solving high-dimensional mean field games (MFG) with normalizing flows (NF) and regularizing NFs with MFG transport costs.

Gradient descent methods for Bayesian variational inference with mean field approximation.

Bayesian Multi-type Mean Field Multi-agent Imitation Learning

Coding for the deep learning project on "Mean Field Analysis of Deep Neural Networks"

Codes for the paper "Mean Field Limit of the Learning Dynamics of Multilayer Neural Networks"