Blogs on Quantum ML » Lamarr Institute

00 Blog Gerlach Thore Qubolite Anleitung - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

qubolite: A Toolbox for Working with QUBO

Thore Gerlach,

31. January 2024

Quadratic unconstrained binary optimization (QUBO) problems appear in many different domains such as Machine Learning and Data Mining. We present our light-weight and feature-rich Python package qubolite for working with QUBO....

|Darstellung der Shapley-Werte zur Erklärung von Merkmalen der Eingabedaten. Die Gatter nehmen dabei die Position von „Spielern“ in einem Koalitionsspiel ein.|Modifizierte Quantenschaltung zur Bestimmung der Beitrag der einzelnen Gatter.

BlogResearch

Explaining Gates in Quantum Circuits with Shapley Values

Sascha Mücke,

22. March 2023

By applying Shapley values to quantum computing, Lamarr scientists seek to explain the role of specific gates in a quantum circuit and give insights into how quantum machine learning models work....

00 Blog Bauckhage ChatGPT Part5 - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

BlogBasics

ChatGPT: A chatbot that can write code?

Prof. Dr. Christian Bauckhage,

24. February 2023

A machine that knows everything and even can program? This very human fantasy now seems to have come true. But is ChatGPT reliable? Our author once again interrogated the language model....

00 Blog Gerlach Evo Annealer neu - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

BlogApplication

Preparing for the quantum age with the IAIS Evo Annealer

Thore Gerlach,

02. November 2022

The IAIS Evo Annealer is a bridging technology for Quantum Computing. With its energy efficiency and the ability to solve large mathematical problems, it can already be used in practice....

00 Blog Muecke Maschinelles Lernen - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

BlogResearch

Quantum random numbers in Machine Learning

Sascha Mücke,

27. October 2021

Due to their stochastic behavior, qubits (quantum bits) can be used as a source of (true) random numbers in Machine Learning. ML2R (now the Lamarr Institute) researchers investigated the use of quantum random numbers to initialize Machine Learning models....

BlogResearch

Evolutionary Optimization of Quantum Circuits

Sascha Mücke,

12. May 2021

Evolutionary optimization is a real alternative to gradient-based methods, as it can be used more flexibly in different application scenarios. Lamarr researchers used evolutionary algorithms to optimize quantum computer circuits....