| 2025 | ICLR | Bayesian Optimization via Continual Variational Last Layer Training. | Paul Brunzema, Mikkel Jordahn, John Willes, Sebastian Trimpe, Jasper Snoek, James Harrison |
| 2025 | ICLR | Offline Hierarchical Reinforcement Learning via Inverse Optimization. | Carolin Schmidt, Daniele Gammelli, James Harrison, Marco Pavone, Filipe Rodrigues |
| 2024 | ICLR | Variational Bayesian Last Layers. | James Harrison, John Willes, Jasper Snoek |
| 2023 | ICML | Graph Reinforcement Learning for Network Control via Bi-Level Optimization. | Daniele Gammelli, James Harrison, Kaidi Yang, Marco Pavone, Filipe Rodrigues, Francisco C. Pereira |
| 2023 | ICRA | Expanding the Deployment Envelope of Behavior Prediction via Adaptive Meta-Learning. | Boris Ivanovic, James Harrison, Marco Pavone |
| 2022 | KDD | Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand. | Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone |
| 2021 | ICML | Deep Reinforcement Learning amidst Continual Structured Non-Stationarity. | Annie Xie, James Harrison, Chelsea Finn |
| 2021 | IROS | Particle MPC for Uncertain and Learning-Based Control. | Robert Dyro, James Harrison, Apoorva Sharma, Marco Pavone |
| 2019 | ICRA | BaRC: Backward Reachability Curriculum for Robotic Reinforcement Learning. | Boris Ivanovic, James Harrison, Apoorva Sharma, Mo Chen, Marco Pavone |
| 2018 | ICRA | Learning Sampling Distributions for Robot Motion Planning. | Brian Ichter, James Harrison, Marco Pavone |
| 2018 | WAFR | Meta-learning Priors for Efficient Online Bayesian Regression. | James Harrison, Apoorva Sharma, Marco Pavone |
| 2017 | ISRR | AdaPT: Zero-Shot Adaptive Policy Transfer for Stochastic Dynamical Systems. | James Harrison, Animesh Garg, Boris Ivanovic, Yuke Zhu, Silvio Savarese, Li Fei-Fei, Marco Pavone |
| 2015 | ICRA | Characterizing device dynamics for haptic manipulation and navigation. | Colin R. Gallacher, James Harrison, Jzsef Kvecses |