Vinzenz Thoma

11 papers A* 4Journal 7
YearRankTypeTitle / Venue / Authors
2026 J jnl
Deep Incentive Design with Differentiable Equilibrium Blocks.
CoRR
Vinzenz Thoma, Georgios Piliouras, Luke Marris
2025 A* conf
Computing Perfect Bayesian Equilibria in Sequential Auctions with Verification.
AAAI
Vinzenz Thoma, Vitor Bosshard, Sven Seuken
2025 A* conf
Learning to Steer Markovian Agents under Model Uncertainty.
ICLR
Jiawei Huang, Vinzenz Thoma, Zebang Shen, Heinrich H. Nax, Niao He
2025 J jnl
Scalable Neural Incentive Design with Parameterized Mean-Field Approximation.
CoRR
Nathan Corecco, Batuhan Yardim, Vinzenz Thoma, Zebang Shen, Niao He
2024 A* conf
Automated Design of Affine Maximizer Mechanisms in Dynamic Settings.
AAAI
Michael J. Curry, Vinzenz Thoma, Darshan Chakrabarti, Stephen McAleer, Christian Kroer, Tuomas Sandholm, Niao He, Sven Seuken
2024 J jnl
Automated Design of Affine Maximizer Mechanisms in Dynamic Settings.
CoRR
Michael J. Curry, Vinzenz Thoma, Darshan Chakrabarti, Stephen McAleer, Christian Kroer, Tuomas Sandholm, Niao He, Sven Seuken
2024 A* conf
Contextual Bilevel Reinforcement Learning for Incentive Alignment.
NeurIPS
Vinzenz Thoma, Barna Pásztor, Andreas Krause, Giorgia Ramponi, Yifan Hu
2024 J jnl
Learning to Steer Markovian Agents under Model Uncertainty.
CoRR
Jiawei Huang, Vinzenz Thoma, Zebang Shen, Heinrich H. Nax, Niao He
2024 J jnl
Stochastic Bilevel Optimization with Lower-Level Contextual Markov Decision Processes.
CoRR
Vinzenz Thoma, Barna Pásztor, Andreas Krause, Giorgia Ramponi, Yifan Hu
2023 J jnl
Computing Perfect Bayesian Equilibria in Sequential Auctions.
CoRR
Vinzenz Thoma, Vitor Bosshard, Sven Seuken
2023 J jnl
Learning Best Response Policies in Dynamic Auctions via Deep Reinforcement Learning.
CoRR
Vinzenz Thoma, Michael J. Curry, Niao He, Sven Seuken