ligerfotis

mvitac

Self-Supervised Visual-Tactile Representation Learning via Multimodal Contrastive Training

maze3d_collaborative

Human-Agent Collaborative Deep Reinforcement Learning

M2CURL

We propose Multimodal Contrastive Unsupervised RL (M2CURL), a method that learns efficient representations from visuotactile data, improving RL convergence speed and performance. M2CURL is versatile, compatible with various RL algorithms, and enhances learning efficiency in manipulation tasks in the Tactile Gym 2 simulator.

CSE6363_Machine_Learning

Machine Learning algorithms from-scratch implementation. It covers most Supervised and Unsupervised algorithms. Homework assignments and Projects for graduate level Machine Learning Course taught by Dr Manfred Huber at UTA during Spring 21

transf_chatbot_metalWOZ

Chatbot based on Multihead Attention on metal WOZ dataset using transfer learning

H-AI_collab_game

Collaborative Reinforcement Learning on Human-Computer shared task

maze_GI_Unity

Maze Game on Unity for Human-Computer Colalboration

maze_RL_v2

crvae

This is the implementation of the paper: "CR-VAE: Contrastive Regularization on Variational Autoencoders for Preventing Posterior Collapse"

pytorch_tutorial

This repository contains a comprehensive tutorial designed to introduce you to the fundamental concepts and usage of the PyTorch library.

representation_learning_tutorial

Implementation of basic autoencoder architectures and SimCLRv2

stock_value_dnn

Stock value regression using DNN on fanancial data of S&P 500 companies

ANAC2015_Boulware_like_agent

A simple agent that follows Boulware-like bid policy (3rd place at domestic tournament at Technical University of Crete)

classic_vision

cnn_torch

collaborative_games

RL-based human robot collaboration in shared tasks on ROS

CSE5306_Distributed_Systems_Project_1

TCP Server-Client communication for text annotation for graduate level Distributed Systems Course taught by Chance Eary at UTA during Spring 21

CSE5306_Distributed_Systems_Project_2

TCP Server-Client communication for text annotation with redundancy and polling for graduate level Distributed Systems Course taught by Chance Eary at UTA during Spring 21

CSE5306_Distributed_Systems_Project_3

TCP Server-Client communication for text annotation with redundancy, polling and back-up server for graduate level Distributed Systems Course taught by Chance Eary at UTA during Spring 21

HumanAgentLunar

LSPI

maze_RL

ML_course

moco_distr

path_planning_manhattan_distance

Path planber using manhattan distance on a known map

robot_dynamics_and_control

Dynamic Parameters Experimental System Identification and PD Controler of a single joint robot

robot_kinematics

Forward and Inverse Kinematics for simulated robot

tactile_gym

Suite of PyBullet reinforcement learning environments targeted towards using tactile data as the main form of observation.

tacto_contrastive

wall_following_goal_seeker_ev3