most citedLearning to Navigate the Web

3 citations · 3 across the 2 of their papers we have counts for

collaborators

5 papers

cs.NE2020

Benchmarking Deep Spiking Neural Networks on Neuromorphic Hardware

Christoph Ostrau, Jonas Homburg, Christian Klarhorst +2

With more and more event-based neuromorphic hardware systems being developed at universities and in industry, there is a growing need for assessing their performance with domain sp…

cs.LG20183 cited

Learning to Navigate the Web

Izzeddin Gur, Ulrich Rueckert, Aleksandra Faust +1

Learning in environments with large state and action spaces, and sparse rewards, can hinder a Reinforcement Learning (RL) agent's learning through trial-and-error. For instance, fo…

cs.LG2018

Coordinated Heterogeneous Distributed Perception based on Latent Space Representation

Timo Korthals, Jürgen Leitner, Ulrich Rückert

We investigate a reinforcement approach for distributed sensing based on the latent space derived from multi-modal deep generative models. Our contribution provides insights to the…

cs.RO2018

Towards Inverse Sensor Mapping in Agriculture

Timo Korthals, Mikkel Kragh, Peter Christiansen +1

In recent years, the drive of the Industry 4.0 initiative has enriched industrial and scientific approaches to build self-driving cars or smart factories. Agricultural applications…

cs.DC2018

Development of Energy Models for Design Space Exploration of Embedded Many-Core Systems

Christian Klarhorst, Martin Flasskamp, Johannes Ax +4

This paper introduces a methodology to develop energy models for the design space exploration of embedded many-core systems. The design process of such systems can benefit from sop…