model-based

Model-based Reinforcement Learning Framework

Customisable Unified Physical Simulations (CUPS) for Reinforcement Learning. Experiments run on the ai2thor environment (http://ai2thor.allenai.org/) e.g. using A3C, RainbowDQN and A3C_GA (Gated Attention multi-modal fusion) for Task-Oriented Language Grounding (tasks specified by natural language instructions) e.g. "Pick up the Cup or else"

CaDM: Context-aware Dynamics Model for Generalization in Model-based Reinforcement Learning

MOBATSim (Model-based Autonomous Traffic Simulation Framework) is a simulation framework based on MATLAB Simulink that allows the user to assess vehicle level and traffic level safety by a 3D traffic simulation. Related MathWorks Online Article: https://www.mathworks.com/company/newsletters/articles/developing-an-autonomous-traffic-simulation-framework-for-functional-safety-testing.html

This repository contains recent research papers, datasets, and source codes (if any) for Group Recommendation

TOmographic MOdel-BAsed Reconstruction (ToMoBAR) software

Model-based Policy Gradients

Expert Advisor based on Falcon Template and kNN trading algorithm

[TIFS 2019] Skeleton-based Gait Recognition via Robust Frame-level Matching (RFM)

Development and simulation framework for Application Specific Vector Processor

Simulation Framework for the Static Scheduler

A collection of Jupyter notebooks on articles and material online related to recommender systems in python.

Signal Processing Toolbox for Calcium Imaging Data

TRADES Tool

BARINEL algorithm - “Spectrum-Based Multiple Fault Localization” with Fuzzy logic

Browser-based MyUI Runtime Implementation

A Python package for Robot Learning

Highway Driving (project 7 of 9 from Udacity Self-Driving Car Engineer Nanodegree)

Layout manager for react applications

This is the code repository for my thesis

User Interface Editors for Model-Based Editors and Domain Specific Languages (DSLs)

Model-based recommendation systems involve building a model based on the dataset of ratings. This approach potentially offers the benefits of both speed and scalability. [Source: http://www.cs.carleton.edu/cs_comps/0607/recommend/recommender/modelbased.html]

Segmentation of France using time series

A Model-based Agent, for chinese speech recognize.

Component-based Assumptions and Restrictions for Dataflow Specifications