Machine Learning and Deep Learning

One of the main research topics of the L3S in the field of artificial intelligence is Machine Learning and Deep Learning.

AlgorithmenkontrolLI

Algorithm control: Efficient learning to control algorithm parameters

BIAS

In BIAS, Experts examine how standards of unbiased attitudes and non-discriminatory practices can be met in big data analysis and algorithm-based decision-making.

DaFne

The DaFne project aims to improve the usability of data generation methods for AI researchers and developers by developing an innovative, flexible data generation platform.

Green AutoML for Driver Assistance Systems

The aim of the GreenAutoML4FAS project is to design a holistic, carbon-efficient system for driver assistance systems

GLACIATION

GLACIATION aims to reduce carbon emissions by developing a distributed knowledge graph that improves the efficiency of big data analysis.

ixAutoML

Making automatic machine learning systems more human-centered by enabling interactivity and explainability.

Leibniz AI Academy

Development and establishment of a transcurricular, cross-disciplinary micro-degree program "Leibniz AI Academy" at Leibniz Universität Hannover (LUH).

LeibnizKILabor

The International Future Lab for AI spends three years researching new topics in AI and developing intelligent solutions for personalised medicine.

NoBIAS

The core objective of NoBIAS is to research and develop novel methods for data-driven decision-making without bias.

Online Optimierung

The goal of the project is to develop and investigate online convex optimization (OCO)-based control schemes for general cost functions and constraints without relying on restrictive assumptions.

ProKI-Hannover

A Germany-wide demonstration and transfer network for the use of artificial intelligence (AI) in production.

PRESENt

The PRESENt consortium uses data-intensive technologies and machine learning for personalized prognosis, prevention and treatment of norovirus infections.

A diverse consortium aiming to unlock the potential of quantum computing for solving complex combinatorial optimisation problems in high-stakes industries such as microchip manufacturing and automotive engineering.

SWIFTT

SWIFTT will provide forest managers with affordable, simple and effective remote sensing tools backed up by powerful machine learning models. It will offer a holistic health monitoring service to detect and map various risks for forests and their managers