most citedResponse Estimation and System Identification of Dynamical Systems via Physics-Informed Neural Networks

2 citations · 2 across the 1 of their papers we have counts for

collaborators
Showing cs.LGShow all

2 papers · 1 filter

cs.LG2025

Deep Belief Markov Models for POMDP Inference

Giacomo Arcieri, Konstantinos G. Papakonstantinou, Daniel Straub +1

This work introduces a novel deep learning-based architecture, termed the Deep Belief Markov Model (DBMM), which provides efficient, model-formulation agnostic inference in Partial…

cs.LG2023

POMDP inference and robust solution via deep reinforcement learning: An application to railway optimal maintenance

Giacomo Arcieri, Cyprien Hoelzl, Oliver Schwery +3

Partially Observable Markov Decision Processes (POMDPs) can model complex sequential decision-making problems under stochastic and uncertain environments. A main reason hindering t…