patrickyanz Goto Github PK

4939_project

academicpages.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

binary_heap

bmi_calcualtor

ddpm

PyTorch DDPM implementation

deep-reinforcement-learning-explained

glass-classification

contains input csv, python notebook for Glass identification through machine learning techniques

gr_data_analysis

Gre Data analysis

highway-env

A minimalist environment for decision-making in autonomous driving

highway-env-1.5

highway-env-1.5

highway_env

metropolis_algorithm_stochastic_process

Monte Carlo Markov Chain (MCMC) is a method used in statistics and statistical physics to extract sequences of random samples from a probability distribution when direct sampling is difficult. We implement the metropolis algorithm to the travelling random walk and reduce the average waiting time for travelers. Prove the Metropolis algorithm and generalize python model to mimic travelers travelling within Canada.

morl-baselines

Multi-Objective Reinforcement Learning algorithms implementations.

morl-smartsystems4u

Multi-Objective Reinforcement Learning sandbox

motion_planning_using_rl

Autonomous Highway Driving using highway-env and Reinforcement Learning agent Deep Q-Network (DQN)

patrickyanz.github.io

Patrick personal website

quantum

Hybrid Quantum-Classical Machine Learning in TensorFlow

single-qubit-rl

sta340_project

tic-tac-toe

Based on two dimensional array