Daniele Gammelli

40 papers A* 3C 1Journal 32Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Accelerating High-Capacity Ridepooling in Robo-Taxi Systems. IEEE Robotics Autom. Lett. Xinling Li, Daniele Gammelli, Alex Wallar, Jinhua Zhao, Gioele Zardini
2026	J	`jnl`	Competitive Multi-Operator Reinforcement Learning for Joint Pricing and Fleet Rebalancing in AMoD Systems. CoRR Emil Kragh Toft, Carolin Schmidt, Daniele Gammelli, Filipe Rodrigues
2026	J	`jnl`	GRAND: Guidance, Rebalancing, and Assignment for Networked Dispatch in Multi-Agent Path Finding. IEEE Robotics Autom. Lett. Johannes Gaber, Meshal Alharbi, Daniele Gammelli, Gioele Zardini
2026	J	`jnl`	Graph Neural Model Predictive Control for High-Dimensional Systems. CoRR Patrick Benito Eberhard, Luis A. Pabon, Daniele Gammelli, Hugo Buurmeijer, Amon Lahr, Mark Leone, Andrea Carron, Marco Pavone
2026	J	`jnl`	Reproducibility in the Control of Autonomous Mobility-on-Demand Systems. IEEE Trans. Robotics Xinling Li, Meshal Alharbi, Daniele Gammelli, James Harrison, Filipe Rodrigues, Maximilian Schiffer, Marco Pavone, Emilio Frazzoli, Jinhua Zhao, Gioele Zardini
2025	J	`jnl`	Agile Tradespace Exploration for Space Rendezvous Mission Design via Transformers. CoRR Yuji Takubo, Daniele Gammelli, Marco Pavone, Simone D'Amico
2025	J	`jnl`	GRAND: Guidance, Rebalancing, and Assignment for Networked Dispatch in Multi-Agent Path Finding. CoRR Johannes Gaber, Meshal Alharbi, Daniele Gammelli, Gioele Zardini
2025	C	`conf`	Generalizable Spacecraft Trajectory Generation via Multimodal Learning with Transformers. ACC Davide Celestini, Amirhossein Afsharrad, Daniele Gammelli, Tommaso Guffanti, Gioele Zardini, Sanjay Lall, Elisa Capello, Simone D'Amico, Marco Pavone
2025	J	`jnl`	Learning Joint Rebalancing and Dynamic Pricing Policies for Autonomous Mobility-on-Demand. IEEE Trans. Intell. Transp. Syst. Xinling Li, Carolin Schmidt, Daniele Gammelli, Filipe Rodrigues
2025	—	`conf`	Learning Traffic Flows: Graph Neural Networks for Metamodelling Traffic Assignment. MT-ITS Oskar Bohn Lassen, Serio Agriesti, Mohamed Eldafrawi, Daniele Gammelli, Guido Cantelmo, Guido Gentile, Francisco Câmara Pereira
2025	J	`jnl`	Learning traffic flows: Graph Neural Networks for Metamodelling Traffic Assignment. CoRR Oskar Bohn Lassen, Serio Agriesti, Mohamed Eldafrawi, Daniele Gammelli, Guido Cantelmo, Guido Gentile, Francisco Câmara Pereira
2025	J	`jnl`	Multi-Timescale Model Predictive Control for Slow-Fast Systems. CoRR Lukas Schroth, Daniel Morton, Amon Lahr, Daniele Gammelli, Andrea Carron, Marco Pavone
2025	A*	`conf`	Offline Hierarchical Reinforcement Learning via Inverse Optimization. ICLR Carolin Schmidt, Daniele Gammelli, James Harrison, Marco Pavone, Filipe Rodrigues
2025	J	`jnl`	Reproducibility in the Control of Autonomous Mobility-on-Demand Systems. CoRR Xinling Li, Meshal Alharbi, Daniele Gammelli, James Harrison, Filipe Rodrigues, Maximilian Schiffer, Marco Pavone, Emilio Frazzoli, Jinhua Zhao, Gioele Zardini
2025	J	`jnl`	Robo-taxi Fleet Coordination at Scale via Reinforcement Learning. CoRR Luigi Tresca, Carolin Schmidt, James Harrison, Filipe Rodrigues, Gioele Zardini, Daniele Gammelli, Marco Pavone
2025	J	`jnl`	Semantic Trajectory Generation for Goal-Oriented Spacecraft Rendezvous. CoRR Yuji Takubo, Arpit Dwivedi, Sukeerth Ramkumar, Luis A. Pabon, Daniele Gammelli, Marco Pavone, Simone D'Amico
2025	J	`jnl`	Vision Foundation Model Embedding-Based Semantic Anomaly Detection. CoRR Max Peter Ronecker, Matthew Foutter, Amine Elhafsi, Daniele Gammelli, Ihor Barakaiev, Marco Pavone, Daniel Watzenig
2024	J	`jnl`	Adapting a Foundation Model for Space-based Tasks. CoRR Matthew Foutter, Praneet Bhoj, Rohan Sinha, Amine Elhafsi, Somrita Banerjee, Christopher Agia, Justin Kruger, Tommaso Guffanti, Daniele Gammelli, Simone D'Amico, Marco Pavone
2024	J	`jnl`	Generalizable Spacecraft Trajectory Generation via Multimodal Learning with Transformers. CoRR Davide Celestini, Amirhossein Afsharrad, Daniele Gammelli, Tommaso Guffanti, Gioele Zardini, Sanjay Lall, Elisa Capello, Simone D'Amico, Marco Pavone
2024	—	`conf`	Learning to Control Autonomous Fleets from Observation via Offline Reinforcement Learning. ECC Carolin Schmidt, Daniele Gammelli, Francisco Câmara Pereira, Filipe Rodrigues
2024	J	`jnl`	Offline Hierarchical Reinforcement Learning via Inverse Optimization. CoRR Carolin Schmidt, Daniele Gammelli, James Harrison, Marco Pavone, Filipe Rodrigues
2024	—	`conf`	Real-Time Control of Electric Autonomous Mobility-on-Demand Systems via Graph Reinforcement Learning. ECC Aaryan Singhal, Daniele Gammelli, Justin Luke, Karthik Gopalakrishnan, Dominik Helmreich, Marco Pavone
2024	J	`jnl`	Towards Robust Spacecraft Trajectory Optimization via Transformers. CoRR Yuji Takubo, Tommaso Guffanti, Daniele Gammelli, Marco Pavone, Simone D'Amico
2024	J	`jnl`	Transformer-Based Model Predictive Control: Trajectory Optimization via Sequence Modeling. IEEE Robotics Autom. Lett. Davide Celestini, Daniele Gammelli, Tommaso Guffanti, Simone D'Amico, Elisa Capello, Marco Pavone
2024	J	`jnl`	Transformer-based Model Predictive Control: Trajectory Optimization via Sequence Modeling. CoRR Davide Celestini, Daniele Gammelli, Tommaso Guffanti, Simone D'Amico, Elisa Capello, Marco Pavone
2023	A*	`conf`	Graph Reinforcement Learning for Network Control via Bi-Level Optimization. ICML Daniele Gammelli, James Harrison, Kaidi Yang, Marco Pavone, Filipe Rodrigues, Francisco C. Pereira
2023	J	`jnl`	Graph Reinforcement Learning for Network Control via Bi-Level Optimization. CoRR Daniele Gammelli, James Harrison, Kaidi Yang, Marco Pavone, Filipe Rodrigues, Francisco C. Pereira
2023	J	`jnl`	Learning to Control Autonomous Fleets from Observation via Offline Reinforcement Learning. CoRR Carolin Schmidt, Daniele Gammelli, Francisco Câmara Pereira, Filipe Rodrigues
2023	J	`jnl`	Real-time Control of Electric Autonomous Mobility-on-Demand Systems via Graph Reinforcement Learning. CoRR Aaryan Singhal, Daniele Gammelli, Justin Luke, Karthik Gopalakrishnan, Dominik Helmreich, Marco Pavone
2023	J	`jnl`	Transformers for Trajectory Optimization with Application to Spacecraft Rendezvous. CoRR Tommaso Guffanti, Daniele Gammelli, Simone D'Amico, Marco Pavone
2022	J	`jnl`	Generalized multi-output Gaussian process censored regression. Pattern Recognit. Daniele Gammelli, Kasper Pryds Rolsted, Dario Pacino, Filipe Rodrigues
2022	A*	`conf`	Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand. KDD Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone
2022	J	`jnl`	Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand. CoRR Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone
2022	J	`jnl`	Recurrent flow networks: A recurrent latent variable model for density estimation of urban mobility. Pattern Recognit. Daniele Gammelli, Filipe Rodrigues
2021	—	`conf`	Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems. CDC Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone
2021	J	`jnl`	Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems. CoRR Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone
2021	J	`jnl`	Predictive and Prescriptive Performance of Bike-Sharing Demand Forecasts for Inventory Management. CoRR Daniele Gammelli, Yihua Wang, Dennis Prak, Filipe Rodrigues, Stefan Minner, Francisco Câmara Pereira
2020	J	`jnl`	Estimating Latent Demand of Shared Mobility through Censored Gaussian Processes. CoRR Daniele Gammelli, Inon Peled, Filipe Rodrigues, Dario Pacino, Haci A. Kurtaran, Francisco C. Pereira
2020	J	`jnl`	Generalized Multi-Output Gaussian Process Censored Regression. CoRR Daniele Gammelli, Kasper Pryds Rolsted, Dario Pacino, Filipe Rodrigues
2020	J	`jnl`	Recurrent Flow Networks: A Recurrent Latent Variable Model for Spatio-Temporal Density Modelling. CoRR Daniele Gammelli, Filipe Rodrigues