MLQD is a Python Package for Machine Learning-based Quantum Dissipative Dynamics
-
Updated
Sep 3, 2024 - Jupyter Notebook
MLQD is a Python Package for Machine Learning-based Quantum Dissipative Dynamics
Quantum machine learning (QML) Core Fortran Functions
Search & KRR & Planning
Speeding up quantum dissipative dynamics of open systems with kernel methods
Data science Mini projects
A proof-of-concept type demo of the Binary Encoded SMARTS Pattern Enumeration + Molecular aCCess System molecular descriptor developed as part of Bachelor's Thesis: "Molecular descriptor engineering for machine learning predictions in atmospheric science." Includes a toy data set for demonstrative purposes.
Implementing ALC Tableau. For an ALC KB and a query given in Negation Normal Form pre-generated, using ALC Tableau to determine whether the query is entailed by the KB.
Murder Mystery Mansion classic mystery game developed using PDDL planning language.
We were provided with a project in Knowledge Representation and Reasoning (KRR) and we have to apply rdf, sparql and make ontology
DST approach on Recommended Systems(RS).
Add a description, image, and links to the krr topic page so that developers can more easily learn about it.
To associate your repository with the krr topic, visit your repo's landing page and select "manage topics."