Adrien Bolland

According to our database1, Adrien Bolland authored at least 18 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Bayesian Inference for Estimating Generation Costs in Electricity Markets.
CoRR, April, 2026

Maximum-Entropy Exploration with Future State-Action Visitation Measures.
CoRR, March, 2026

Gym-TORAX: Open-source software for integrating reinforcement learning with plasma control simulators in tokamak research.
Softw. Impacts, 2026

2025
Gym-TORAX: Open-source software for integrating RL with plasma control simulators.
CoRR, October, 2025

SecuLEx: a Secure Limit Exchange Market for Dynamic Operating Envelopes.
CoRR, October, 2025

Reimagining Exploration: Theoretical Insights and Practical Advancements in Policy Gradient Methods.
PhD thesis, 2025

2024
Off-Policy Maximum Entropy RL with Future State and Action Visitation Measures.
CoRR, 2024

Costs Estimation in Unit Commitment Problems using Simulation-Based Inference.
CoRR, 2024

Reinforcement Learning for Efficient Design and Control Co-optimisation of Energy Systems.
CoRR, 2024

Behind the Myth of Exploration in Policy Gradients.
CoRR, 2024

Optimal Control of Renewable Energy Communities subject to Network Peak Fees with Model Predictive Control and Reinforcement Learning Algorithms.
CoRR, 2024

Informed POMDP: Leveraging Additional Information in Model-Based RL.
RLJ, 2024

2023
Policy Gradient Algorithms Implicitly Optimize by Continuation.
Trans. Mach. Learn. Res., 2023

Distributional reinforcement learning with unconstrained monotonic neural networks.
Neurocomputing, 2023

2022
Recurrent networks, hidden states and beliefs in partially observable environments.
Trans. Mach. Learn. Res., 2022

Jointly Learning Environments and Control Policies with Projected Stochastic Gradient Ascent.
J. Artif. Intell. Res., 2022

2021
A deep reinforcement learning framework for continuous intraday market bidding.
Mach. Learn., 2021

2020
Learning optimal environments using projected stochastic gradient ascent.
CoRR, 2020


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