Computing Perfect Bayesian Equilibria in Sequential Auctions. - Vinzenz Thoma; Vitor Bosshard; Sven Seuken (CoRR, 2023)

Learning Best Response Policies in Dynamic Auctions via Deep Reinforcement Learning. - Vinzenz Thoma; Michael J. Curry; Niao He; Sven Seuken (CoRR, 2023)

Automated Design of Affine Maximizer Mechanisms in Dynamic Settings. - Michael J. Curry; Vinzenz Thoma; Darshan Chakrabarti; Stephen McAleer; Christian Kroer; Tuomas Sandholm; Niao He; Sven Seuken (AAAI, 2024)

Contextual Bilevel Reinforcement Learning for Incentive Alignment. - Vinzenz Thoma; Barna Pásztor; Andreas Krause 001; Giorgia Ramponi; Yifan Hu (NeurIPS, 2024)

Stochastic Bilevel Optimization with Lower-Level Contextual Markov Decision Processes. - Vinzenz Thoma; Barna Pásztor; Andreas Krause 001; Giorgia Ramponi; Yifan Hu (CoRR, 2024)

Computing Perfect Bayesian Equilibria in Sequential Auctions with Verification. - Vinzenz Thoma; Vitor Bosshard; Sven Seuken (AAAI, 2025)

Learning to Steer Markovian Agents under Model Uncertainty. - Jiawei Huang; Vinzenz Thoma; Zebang Shen; Heinrich H. Nax; Niao He (ICLR, 2025)