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ORCIDDaniele Gammelli
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2020 – today
- 2026
[j7]Xinling Li
, Daniele Gammelli, Alex Wallar, Jinhua Zhao, Gioele Zardini:
Accelerating High-Capacity Ridepooling in Robo-Taxi Systems. IEEE Robotics Autom. Lett. 11(3): 2450-2457 (2026)- [j6]Johannes Gaber, Meshal Alharbi, Daniele Gammelli, Gioele Zardini:
GRAND: Guidance, Rebalancing, and Assignment for Networked Dispatch in Multi-Agent Path Finding. IEEE Robotics Autom. Lett. 11(5): 5470-5477 (2026) - [j5]Xinling Li, Meshal Alharbi, Daniele Gammelli, James Harrison, Filipe Rodrigues, Maximilian Schiffer, Marco Pavone, Emilio Frazzoli, Jinhua Zhao, Gioele Zardini:
Reproducibility in the Control of Autonomous Mobility-on-Demand Systems. IEEE Trans. Robotics 42: 1428-1447 (2026) - [i26]Patrick Benito Eberhard, Luis A. Pabon, Daniele Gammelli, Hugo Buurmeijer, Amon Lahr, Mark Leone, Andrea Carron, Marco Pavone:
Graph Neural Model Predictive Control for High-Dimensional Systems. CoRR abs/2602.17601 (2026) - [i25]Emil Kragh Toft, Carolin Schmidt, Daniele Gammelli, Filipe Rodrigues:
Competitive Multi-Operator Reinforcement Learning for Joint Pricing and Fleet Rebalancing in AMoD Systems. CoRR abs/2603.05000 (2026) - [i24]Eleanor Brosius, Yuji Takubo, Daniele Gammelli, Simone D'Amico, Marco Pavone:
Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models. CoRR abs/2606.04123 (2026) - 2025
- [j4]Xinling Li, Carolin Schmidt, Daniele Gammelli, Filipe Rodrigues:
Learning Joint Rebalancing and Dynamic Pricing Policies for Autonomous Mobility-on-Demand. IEEE Trans. Intell. Transp. Syst. 26(10): 16619-16634 (2025) - [c8]Davide Celestini, Amirhossein Afsharrad, Daniele Gammelli, Tommaso Guffanti, Gioele Zardini, Sanjay Lall, Elisa Capello, Simone D'Amico, Marco Pavone:
Generalizable Spacecraft Trajectory Generation via Multimodal Learning with Transformers. ACC 2025: 3558-3565 - [c7]Carolin Schmidt, Daniele Gammelli, James Harrison, Marco Pavone, Filipe Rodrigues:
Offline Hierarchical Reinforcement Learning via Inverse Optimization. ICLR 2025 - [c6]Oskar Bohn Lassen, Serio Agriesti, Mohamed Eldafrawi, Daniele Gammelli, Guido Cantelmo, Guido Gentile, Francisco Câmara Pereira:
Learning Traffic Flows: Graph Neural Networks for Metamodelling Traffic Assignment. MT-ITS 2025: 1-8 - [i23]Luigi Tresca, Carolin Schmidt, James Harrison, Filipe Rodrigues, Gioele Zardini, Daniele Gammelli, Marco Pavone:
Robo-taxi Fleet Coordination at Scale via Reinforcement Learning. CoRR abs/2504.06125 (2025) - [i22]Max Peter Ronecker, Matthew Foutter, Amine Elhafsi, Daniele Gammelli, Ihor Barakaiev, Marco Pavone, Daniel Watzenig:
Vision Foundation Model Embedding-Based Semantic Anomaly Detection. CoRR abs/2505.07998 (2025) - [i21]Oskar Bohn Lassen, Serio Agriesti, Mohamed Eldafrawi, Daniele Gammelli, Guido Cantelmo, Guido Gentile, Francisco Câmara Pereira:
Learning traffic flows: Graph Neural Networks for Metamodelling Traffic Assignment. CoRR abs/2505.11230 (2025) - [i20]Xinling Li, Meshal Alharbi, Daniele Gammelli, James Harrison, Filipe Rodrigues, Maximilian Schiffer, Marco Pavone, Emilio Frazzoli, Jinhua Zhao, Gioele Zardini:
Reproducibility in the Control of Autonomous Mobility-on-Demand Systems. CoRR abs/2506.07345 (2025) - [i19]Yuji Takubo, Daniele Gammelli, Marco Pavone, Simone D'Amico:
Agile Tradespace Exploration for Space Rendezvous Mission Design via Transformers. CoRR abs/2510.03544 (2025) - [i18]Lukas Schroth, Daniel Morton, Amon Lahr, Daniele Gammelli, Andrea Carron, Marco Pavone:
Multi-Timescale Model Predictive Control for Slow-Fast Systems. CoRR abs/2511.14311 (2025) - [i17]Johannes Gaber, Meshal Alharbi, Daniele Gammelli, Gioele Zardini:
GRAND: Guidance, Rebalancing, and Assignment for Networked Dispatch in Multi-Agent Path Finding. CoRR abs/2512.03194 (2025) - [i16]Yuji Takubo, Arpit Dwivedi, Sukeerth Ramkumar, Luis A. Pabon, Daniele Gammelli, Marco Pavone, Simone D'Amico:
Semantic Trajectory Generation for Goal-Oriented Spacecraft Rendezvous. CoRR abs/2512.09111 (2025) - 2024
- [j3]Davide Celestini, Daniele Gammelli, Tommaso Guffanti, Simone D'Amico, Elisa Capello, Marco Pavone:
Transformer-Based Model Predictive Control: Trajectory Optimization via Sequence Modeling. IEEE Robotics Autom. Lett. 9(11): 9820-9827 (2024) - [c5]Carolin Schmidt, Daniele Gammelli, Francisco Câmara Pereira, Filipe Rodrigues:
Learning to Control Autonomous Fleets from Observation via Offline Reinforcement Learning. ECC 2024: 1399-1406 - [c4]Aaryan Singhal, Daniele Gammelli, Justin Luke, Karthik Gopalakrishnan, Dominik Helmreich, Marco Pavone:
Real-Time Control of Electric Autonomous Mobility-on-Demand Systems via Graph Reinforcement Learning. ECC 2024: 1407-1414 - [i15]Matthew Foutter, Praneet Bhoj, Rohan Sinha, Amine Elhafsi, Somrita Banerjee, Christopher Agia, Justin Kruger, Tommaso Guffanti, Daniele Gammelli, Simone D'Amico, Marco Pavone:
Adapting a Foundation Model for Space-based Tasks. CoRR abs/2408.05924 (2024) - [i14]Yuji Takubo, Tommaso Guffanti, Daniele Gammelli, Marco Pavone, Simone D'Amico:
Towards Robust Spacecraft Trajectory Optimization via Transformers. CoRR abs/2410.05585 (2024) - [i13]Carolin Schmidt, Daniele Gammelli, James Harrison, Marco Pavone, Filipe Rodrigues:
Offline Hierarchical Reinforcement Learning via Inverse Optimization. CoRR abs/2410.07933 (2024) - [i12]Davide Celestini, Amirhossein Afsharrad, Daniele Gammelli, Tommaso Guffanti, Gioele Zardini, Sanjay Lall, Elisa Capello, Simone D'Amico, Marco Pavone:
Generalizable Spacecraft Trajectory Generation via Multimodal Learning with Transformers. CoRR abs/2410.11723 (2024) - [i11]Davide Celestini, Daniele Gammelli, Tommaso Guffanti, Simone D'Amico, Elisa Capello, Marco Pavone:
Transformer-based Model Predictive Control: Trajectory Optimization via Sequence Modeling. CoRR abs/2410.23916 (2024) - 2023
- [c3]Daniele Gammelli, James Harrison, Kaidi Yang, Marco Pavone, Filipe Rodrigues, Francisco C. Pereira:
Graph Reinforcement Learning for Network Control via Bi-Level Optimization. ICML 2023: 10587-10610 - [i10]Carolin Schmidt, Daniele Gammelli, Francisco Câmara Pereira, Filipe Rodrigues:
Learning to Control Autonomous Fleets from Observation via Offline Reinforcement Learning. CoRR abs/2302.14833 (2023) - [i9]Daniele Gammelli, James Harrison, Kaidi Yang, Marco Pavone, Filipe Rodrigues, Francisco C. Pereira:
Graph Reinforcement Learning for Network Control via Bi-Level Optimization. CoRR abs/2305.09129 (2023) - [i8]Tommaso Guffanti, Daniele Gammelli, Simone D'Amico, Marco Pavone:
Transformers for Trajectory Optimization with Application to Spacecraft Rendezvous. CoRR abs/2310.13831 (2023) - [i7]Aaryan Singhal, Daniele Gammelli, Justin Luke, Karthik Gopalakrishnan, Dominik Helmreich, Marco Pavone:
Real-time Control of Electric Autonomous Mobility-on-Demand Systems via Graph Reinforcement Learning. CoRR abs/2311.05780 (2023) - 2022
- [j2]Daniele Gammelli, Kasper Pryds Rolsted, Dario Pacino, Filipe Rodrigues:
Generalized multi-output Gaussian process censored regression. Pattern Recognit. 129: 108751 (2022) - [j1]Daniele Gammelli, Filipe Rodrigues:
Recurrent flow networks: A recurrent latent variable model for density estimation of urban mobility. Pattern Recognit. 129: 108752 (2022) - [c2]Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone:
Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand. KDD 2022: 2913-2923 - [i6]Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone:
Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand. CoRR abs/2202.07147 (2022) - 2021
- [c1]Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone:
Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems. CDC 2021: 2996-3003 - [i5]Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone:
Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems. CoRR abs/2104.11434 (2021) - [i4]Daniele Gammelli, Yihua Wang, Dennis Prak, Filipe Rodrigues, Stefan Minner, Francisco Câmara Pereira:
Predictive and Prescriptive Performance of Bike-Sharing Demand Forecasts for Inventory Management. CoRR abs/2108.00858 (2021) - 2020
- [i3]Daniele Gammelli, Inon Peled, Filipe Rodrigues, Dario Pacino, Haci A. Kurtaran, Francisco C. Pereira:
Estimating Latent Demand of Shared Mobility through Censored Gaussian Processes. CoRR abs/2001.07402 (2020) - [i2]Daniele Gammelli, Filipe Rodrigues:
Recurrent Flow Networks: A Recurrent Latent Variable Model for Spatio-Temporal Density Modelling. CoRR abs/2006.05256 (2020) - [i1]Daniele Gammelli, Kasper Pryds Rolsted, Dario Pacino, Filipe Rodrigues:
Generalized Multi-Output Gaussian Process Censored Regression. CoRR abs/2009.04822 (2020)
Coauthor Index
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last updated on 2026-07-12 23:53 CEST by the dblp team
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