James Harrison

69 papers A* 16A 1C 3Journal 43Unranked 6
YearRankTypeTitle / Venue / Authors
2026 J jnl
Practical Deep Heteroskedastic Regression.
CoRR
Mikkel Jordahn, Jonas Vestergaard Jensen, James Harrison, Michael Riis Andersen, Mikkel N. Schmidt
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
2026 J jnl
Target-Aligned Reinforcement Learning.
CoRR
Leonard S. Pleiss, James Harrison, Maximilian Schiffer
2025 A* conf
Bayesian Optimization via Continual Variational Last Layer Training.
ICLR
Paul Brunzema, Mikkel Jordahn, John Willes, Sebastian Trimpe, Jasper Snoek, James Harrison
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
2024 J jnl
Applications of fractional calculus in learned optimization.
CoRR
Teodor Alexandru Szente, James Harrison, Mihai Zanfir, Cristian Sminchisescu
2024 J jnl
Bayesian Embeddings for Few-Shot Open World Recognition.
IEEE Trans. Pattern Anal. Mach. Intell.
John Willes, James Harrison, Ali Harakeh, Chelsea Finn, Marco Pavone, Steven L. Waslander
2024 J jnl
Bayesian Optimization via Continual Variational Last Layer Training.
CoRR
Paul Brunzema, Mikkel Jordahn, John Willes, Sebastian Trimpe, Jasper Snoek, James Harrison
2024 J jnl
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models.
Trans. Mach. Learn. Res.
Avi Singh, John D. Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J. Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron T. Parisi, Abhishek Kumar, Alexander A. Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin Fathy Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura Culp, Lechao Xiao, Maxwell L. Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yundi Qian, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel
2024 A* conf
Long-Horizon Planning for Multi-Agent Robots in Partially Observable Environments.
NeurIPS
Siddharth Nayak, Adelmo Morrison Orozco, Marina Ten Have, Jackson Zhang, Vittal Thirumalai, Darren Chen, Aditya Kapoor, Eric Robinson, Karthik Gopalakrishnan, James Harrison, Anuj Mahajan, Brian Ichter, Hamsa Balakrishnan
2024 J jnl
Long-Horizon Planning for Multi-Agent Robots in Partially Observable Environments.
CoRR
Siddharth Nayak, Adelmo Morrison Orozco, Marina Ten Have, Vittal Thirumalai, Jackson Zhang, Darren Chen, Aditya Kapoor, Eric Robinson, Karthik Gopalakrishnan, James Harrison, Brian Ichter, Anuj Mahajan, Hamsa Balakrishnan
2024 J jnl
Offline Hierarchical Reinforcement Learning via Inverse Optimization.
CoRR
Carolin Schmidt, Daniele Gammelli, James Harrison, Marco Pavone, Filipe Rodrigues
2024 J jnl
Risk-Sensitive Soft Actor-Critic for Robust Deep Reinforcement Learning under Distribution Shifts.
CoRR
Tobias Enders, James Harrison, Maximilian Schiffer
2024 A* conf
Universal Neural Functionals.
NeurIPS
Allan Zhou, Chelsea Finn, James Harrison
2024 J jnl
Universal Neural Functionals.
CoRR
Allan Zhou, Chelsea Finn, James Harrison
2024 A* conf
Variational Bayesian Last Layers.
ICLR
James Harrison, John Willes, Jasper Snoek
2024 J jnl
Variational Bayesian Last Layers.
CoRR
James Harrison, John Willes, Jasper Snoek
2023 J jnl
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models.
CoRR
Avi Singh, John D. Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J. Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron Parisi, Abhishek Kumar, Alex Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin F. Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura Culp, Lechao Xiao, Maxwell L. Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yundi Qian, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel
2023 A* conf
Expanding the Deployment Envelope of Behavior Prediction via Adaptive Meta-Learning.
ICRA
Boris Ivanovic, James Harrison, 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 — conf
Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems.
L4DC
Tobias Enders, James Harrison, Marco Pavone, Maximilian Schiffer
2023 J jnl
Multivariate Analysis of Gaze Behavior and Task Performance Within Interface Design Evaluation.
IEEE Trans. Hum. Mach. Syst.
James Blundell, Charlotte Collins, Rod Sears, Tassos Plioutsias, John Huddlestone, Don Harris, James Harrison, Anthony Kershaw, Paul Harrison, Phil Lamb
2023 J jnl
Noise-Reuse in Online Evolution Strategies.
CoRR
Oscar Li, James Harrison, Jascha Sohl-Dickstein, Virginia Smith, Luke Metz
2023 A* conf
Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies.
NeurIPS
Oscar Li, James Harrison, Jascha Sohl-Dickstein, Virginia Smith, Luke Metz
2022 A* conf
A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases.
NeurIPS
James Harrison, Luke Metz, Jascha Sohl-Dickstein
2022 J jnl
A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases.
CoRR
James Harrison, Luke Metz, Jascha Sohl-Dickstein
2022 J jnl
Adaptive Robust Model Predictive Control via Uncertainty Cancellation.
CoRR
Rohan Sinha, James Harrison, Spencer M. Richards, Marco Pavone
2022 C conf
Adaptive Robust Model Predictive Control with Matched and Unmatched Uncertainty.
ACC
Rohan Sinha, James Harrison, Spencer M. Richards, Marco Pavone
2022 J jnl
Expanding the Deployment Envelope of Behavior Prediction via Adaptive Meta-Learning.
CoRR
Boris Ivanovic, James Harrison, Marco Pavone
2022 J jnl
General-Purpose In-Context Learning by Meta-Learning Transformers.
CoRR
Louis Kirsch, James Harrison, Jascha Sohl-Dickstein, Luke Metz
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
Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems.
CoRR
Tobias Enders, James Harrison, Marco Pavone, Maximilian Schiffer
2022 — conf
Practical Tradeoffs between Memory, Compute, and Performance in Learned Optimizers.
CoLLAs
Luke Metz, C. Daniel Freeman, James Harrison, Niru Maheswaranathan, Jascha Sohl-Dickstein
2022 J jnl
Practical tradeoffs between memory, compute, and performance in learned optimizers.
CoRR
Luke Metz, C. Daniel Freeman, James Harrison, Niru Maheswaranathan, Jascha Sohl-Dickstein
2022 J jnl
Safe Active Dynamics Learning and Control: A Sequential Exploration-Exploitation Framework.
IEEE Trans. Robotics
Thomas Lew, Apoorva Sharma, James Harrison, Andrew Bylard, Marco Pavone
2022 J jnl
VeLO: Training Versatile Learned Optimizers by Scaling Up.
CoRR
Luke Metz, James Harrison, C. Daniel Freeman, Amil Merchant, Lucas Beyer, James Bradbury, Naman Agrawal, Ben Poole, Igor Mordatch, Adam Roberts, Jascha Sohl-Dickstein
2021 J jnl
Adaptive Robust Model Predictive Control with Matched and Unmatched Uncertainty.
CoRR
Rohan Sinha, James Harrison, Spencer M. Richards, Marco Pavone
2021 J jnl
Bayesian Embeddings for Few-Shot Open World Recognition.
CoRR
John Willes, James Harrison, Ali Harakeh, Chelsea Finn, Marco Pavone, Steven Lake Waslander
2021 A* conf
Deep Reinforcement Learning amidst Continual Structured Non-Stationarity.
ICML
Annie Xie, James Harrison, Chelsea Finn
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
Network offloading policies for cloud robotics: a learning-based approach.
Auton. Robots
Sandeep Chinchali, Apoorva Sharma, James Harrison, Amine Elhafsi, Daniel Kang, Evgenya Pergament, Eyal Cidon, Sachin Katti, Marco Pavone
2021 J jnl
On the Problem of Reformulating Systems with Uncertain Dynamics as a Stochastic Differential Equation.
CoRR
Thomas Lew, Apoorva Sharma, James Harrison, Edward Schmerling, Marco Pavone
2021 A conf
Particle MPC for Uncertain and Learning-Based Control.
IROS
Robert Dyro, James Harrison, Apoorva Sharma, Marco Pavone
2021 J jnl
Particle MPC for Uncertain and Learning-Based Control.
CoRR
Robert Dyro, James Harrison, Apoorva Sharma, Marco Pavone
2020 J jnl
Adaptive Meta-Learning for Identification of Rover-Terrain Dynamics.
CoRR
Somrita Banerjee, James Harrison, P. Michael Furlong, Marco Pavone
2020 A* conf
Continuous Meta-Learning without Tasks.
NeurIPS
James Harrison, Apoorva Sharma, Chelsea Finn, Marco Pavone
2020 J jnl
Deep Reinforcement Learning amidst Lifelong Non-Stationarity.
CoRR
Annie Xie, James Harrison, Chelsea Finn
2020 J jnl
Safe Model-Based Meta-Reinforcement Learning: A Sequential Exploration-Exploitation Framework.
CoRR
Thomas Lew, Apoorva Sharma, James Harrison, Marco Pavone
2019 A* conf
BaRC: Backward Reachability Curriculum for Robotic Reinforcement Learning.
ICRA
Boris Ivanovic, James Harrison, Apoorva Sharma, Mo Chen, Marco Pavone
2019 J jnl
Continuous Meta-Learning without Tasks.
CoRR
James Harrison, Apoorva Sharma, Chelsea Finn, Marco Pavone
2019 — conf
Network Offloading Policies for Cloud Robotics: A Learning-Based Approach.
Robotics: Science and Systems
Sandeep Chinchali, Apoorva Sharma, James Harrison, Amine Elhafsi, Daniel Kang, Evgenya Pergament, Eyal Cidon, Sachin Katti, Marco Pavone
2019 J jnl
Network Offloading Policies for Cloud Robotics: a Learning-based Approach.
CoRR
Sandeep Chinchali, Apoorva Sharma, James Harrison, Amine Elhafsi, Daniel Kang, Evgenya Pergament, Eyal Cidon, Sachin Katti, Marco Pavone
2019 A* conf
Robust and Adaptive Planning under Model Uncertainty.
ICAPS
Apoorva Sharma, James Harrison, Matthew Tsao, Marco Pavone
2019 J jnl
Robust and Adaptive Planning under Model Uncertainty.
CoRR
Apoorva Sharma, James Harrison, Matthew Tsao, Marco Pavone
2018 J jnl
BaRC: Backward Reachability Curriculum for Robotic Reinforcement Learning.
CoRR
Boris Ivanovic, James Harrison, Apoorva Sharma, Mo Chen, Marco Pavone
2018 A* conf
Learning Sampling Distributions for Robot Motion Planning.
ICRA
Brian Ichter, James Harrison, Marco Pavone
2018 J jnl
Meta-Learning Priors for Efficient Online Bayesian Regression.
CoRR
James Harrison, Apoorva Sharma, Marco Pavone
2018 C conf
Meta-learning Priors for Efficient Online Bayesian Regression.
WAFR
James Harrison, Apoorva Sharma, Marco Pavone
2017 J jnl
ADAPT: Zero-Shot Adaptive Policy Transfer for Stochastic Dynamical Systems.
CoRR
James Harrison, Animesh Garg, Boris Ivanovic, Yuke Zhu, Silvio Savarese, Li Fei-Fei, Marco Pavone
2017 C conf
AdaPT: Zero-Shot Adaptive Policy Transfer for Stochastic Dynamical Systems.
ISRR
James Harrison, Animesh Garg, Boris Ivanovic, Yuke Zhu, Silvio Savarese, Li Fei-Fei, Marco Pavone
2017 J jnl
Learning Sampling Distributions for Robot Motion Planning.
CoRR
Brian Ichter, James Harrison, Marco Pavone
2015 A* conf
Characterizing device dynamics for haptic manipulation and navigation.
ICRA
Colin R. Gallacher, James Harrison, József Kövecses
2004 — conf
Implementation and Evaluation of a Negation Tagger in a Pipeline-based System for Information Extraction from Pathology Reports.
MedInfo
Kevin J. Mitchell, Michael J. Becich, Jules J. Berman, Wendy W. Chapman, John R. Gilbertson, Dilip Gupta, James Harrison, Elizabeth Legowski, Rebecca S. Crowley
1999 — conf
Efficient Multi-Object Dynamic Query Histograms.
INFOVIS
Mark Derthick, James Harrison, Andrew Moore, Steven F. Roth