137 citations · 510 across the 88 of their papers we have counts for
6 papers · 1 filter
Real-Time Recurrent Reinforcement Learning
Julian Lemmel, Radu Grosu
We introduce a biologically plausible RL framework for solving tasks in partially observable Markov decision processes (POMDPs). The proposed algorithm combines three integral part…
Learning Adaptive Safety for Multi-Agent Systems
Luigi Berducci, Shuo Yang, Rahul Mangharam +1
Ensuring safety in dynamic multi-agent systems is challenging due to limited information about the other agents. Control Barrier Functions (CBFs) are showing promise for safety ass…
Enhancing Robot Learning through Learned Human-Attention Feature Maps
Daniel Scheuchenstuhl, Stefan Ulmer, Felix Resch +2
Robust and efficient learning remains a challenging problem in robotics, in particular with complex visual inputs. Inspired by human attention mechanism, with which we quickly proc…
Prediction of Tourism Flow with Sparse Geolocation Data
Julian Lemmel, Zahra Babaiee, Marvin Kleinlehner +5
Modern tourism in the 21st century is facing numerous challenges. Among these the rapidly growing number of tourists visiting space-limited regions like historical cities, museums…
Robustness Analysis of Continuous-Depth Models with Lagrangian Techniques
Sophie A. Neubauer, Radu Grosu
This paper presents, in a unified fashion, deterministic as well as statistical Lagrangian-verification techniques. They formally quantify the behavioral robustness of any time-con…
On the Benefits of Biophysical Synapses
Julian Lemmel, Radu Grosu
The approximation capability of ANNs and their RNN instantiations, is strongly correlated with the number of parameters packed into these networks. However, the complexity barrier…