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Daniele Gammelli
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Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems
D Gammelli, K Yang, J Harrison, F Rodrigues, FC Pereira, M Pavone
IEEE Conference on Decision and Control (CDC), 2021
612021
Considering patient clinical history impacts performance of machine learning models in predicting course of multiple sclerosis
R Seccia, D Gammelli, F Dominici, S Romano, AC Landi, M Salvetti, ...
PloS one 15 (3), e0230219, 2020
552020
Estimating Latent Demand of Shared Mobility through Censored Gaussian Processes
D Gammelli, I Peled, F Rodrigues, D Pacino, HA Kurtaran, FC Pereira
Transportation Research Part C: Emerging Technologies 120, 2020
512020
Predictive and Prescriptive Performance of Bike-Sharing Demand Forecasts for Inventory Management
D Gammelli, Y Wang, D Prak, F Rodrigues, S Minner, FC Pereira
Transportation Research Part C: Emerging Technologies, 2021
372021
Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand
D Gammelli, K Yang, J Harrison, F Rodrigues, F Pereira, C., M Pavone
ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2022
222022
Generalized Multi-Output Gaussian Process Censored Regression
D Gammelli, K Pryds Rolsted, D Pacino, R Filipe
Pattern Recognition 129, 2020
152020
Recurrent Flow Networks: A Recurrent Latent Variable Model for Spatio-Temporal Density Modelling
D Gammelli, F Rodrigues
Pattern Recognition, 2020
11*2020
Transformers for Trajectory Optimization with Application to Spacecraft Rendezvous
T Guffanti, D Gammelli, S D'Amico, M Pavone
IEEE Aerospace Conference, 2023
72023
Graph Reinforcement Learning for Network Control via Bi-Level Optimization
D Gammelli, J Harrison, K Yang, M Pavone, F Rodrigues, FC Pereira
International Conference on Machine Learning (ICML), 2023
42023
Learning to control autonomous fleets from observation via offline reinforcement learning
C Schmidt, D Gammelli, FC Pereira, F Rodrigues
2024 European Control Conference (ECC), 1399-1406, 2024
32024
A Machine Learning Approach to Censored Bike-Sharing Demand Modeling
D Gammelli, F Rodrigues, D Pacino, HA Kurtaran, FC Pereira
Transportation Research Board. Annual Meeting Proceedings 2020, 2020
32020
Transformer-based Model Predictive Control: Trajectory Optimization via Sequence Modeling
D Celestini, D Gammelli, T Guffanti, S D'Amico, E Capello, M Pavone
IEEE Robotics and Automation Letters, 2024
12024
Offline Hierarchical Reinforcement Learning via Inverse Optimization
C Schmidt, D Gammelli, J Harrison, M Pavone, F Rodrigues
arXiv preprint arXiv:2410.07933, 2024
2024
Towards Robust Spacecraft Trajectory Optimization via Transformers
Y Takubo, T Guffanti, D Gammelli, M Pavone, S D'Amico
arXiv preprint arXiv:2410.05585, 2024
2024
Adapting a Foundation Model for Space-based Tasks
M Foutter, P Bhoj, R Sinha, A Elhafsi, S Banerjee, C Agia, J Kruger, ...
arXiv preprint arXiv:2408.05924, 2024
2024
Real-time Control of Electric Autonomous Mobility-on-Demand Systems via Graph Reinforcement Learning
A Singhal, D Gammelli, J Luke, K Gopalakrishnan, D Helmreich, ...
2024 European Control Conference (ECC), 1407-1414, 2024
2024
Reinforcement Learning for Autonomous Mobility-on-Demand Systems: Udvidet resumé
D Gammelli, K Yang, J Harrison, F Rodrigues, FC Pereira, M Pavone
Proceedings from the Annual Transport Conference at Aalborg University 29, 2022
2022
Learning and Control for Adaptive Transportation Systems
D Gammelli
Technical University of Denmark, 2022
2022
Modeling Transport Data Under Stochastic and Latent Censorship
I Peled, D Gammelli, F Rodrigues, D Pacino, FC Pereira
2020
Benchmarking Reinforcement Learning for Network-level Coordination of Autonomous Mobility-on-Demand Systems Across Scales
L Tresca, D Gammelli, J Harrison, G Zardini, M Pavone
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Artikelen 1–20