40 citations · 122 across the 19 of their papers we have counts for
4 papers · 1 filter
Position: Current Benchmarking Hinders Real Progress in Deep Learning for Time Series Forecasting
Valentina Moretti, Ivan Marisca, Cesare Alippi +1
Deep learning models have grown popular in time series applications. However, the large quantity of newly proposed architectures and the often contradictory empirical results make…
Hierarchical Message-Passing Policies for Multi-Agent Reinforcement Learning
Tommaso Marzi, Cesare Alippi, Andrea Cini
Decentralized Multi-Agent Reinforcement Learning (MARL) methods allow for learning scalable multi-agent policies, but suffer from partial observability and induced non-stationarity…
Learning to Predict Global Atrial Fibrillation Dynamics from Sparse Measurements
Alexander Jenkins, Andrea Cini, Joseph Barker +10
Catheter ablation of Atrial Fibrillation (AF) consists of a one-size-fits-all treatment with limited success in persistent AF. This may be due to our inability to map the dynamics…
Relational Conformal Prediction for Correlated Time Series
Andrea Cini, Alexander Jenkins, Danilo Mandic +2
We address the problem of uncertainty quantification in time series forecasting by exploiting observations at correlated sequences. Relational deep learning methods leveraging grap…