Daniele Gammelli

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 17

Top Topics

Reinforcement Learning

Top Venues

Pattern Recognit.

Publications

Carolin Schmidt, Daniele Gammelli, Francisco Câmara Pereira, Filipe Rodrigues
Learning to Control Autonomous Fleets from Observation via Offline Reinforcement Learning. ECC (2024)
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)
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)
Daniele Gammelli, James Harrison, Kaidi Yang, Marco Pavone, Filipe Rodrigues, Francisco C. Pereira
Graph Reinforcement Learning for Network Control via Bi-Level Optimization. CoRR (2023)
Tommaso Guffanti, Daniele Gammelli, Simone D'Amico, Marco Pavone
Transformers for Trajectory Optimization with Application to Spacecraft Rendezvous. CoRR (2023)
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 (2023)
Carolin Schmidt, Daniele Gammelli, Francisco Câmara Pereira, Filipe Rodrigues
Learning to Control Autonomous Fleets from Observation via Offline Reinforcement Learning. CoRR (2023)
Daniele Gammelli, Kasper Pryds Rolsted, Dario Pacino, Filipe Rodrigues
Generalized multi-output Gaussian process censored regression. Pattern Recognit. 129 (2022)
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)
Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone
Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand. CoRR (2022)
Daniele Gammelli, Filipe Rodrigues
Recurrent flow networks: A recurrent latent variable model for density estimation of urban mobility. Pattern Recognit. 129 (2022)
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 (2021)
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 (2021)
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)
Daniele Gammelli, Kasper Pryds Rolsted, Dario Pacino, Filipe Rodrigues
Generalized Multi-Output Gaussian Process Censored Regression. CoRR (2020)
Daniele Gammelli, Filipe Rodrigues
Recurrent Flow Networks: A Recurrent Latent Variable Model for Spatio-Temporal Density Modelling. CoRR (2020)
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 (2020)