Equilibrium Learning in Combinatorial Auctions: Computing Approximate Bayesian Nash Equilibria via Pseudogradient Dynamics. - Stefan Heidekrüger; Paul Sutterer; Nils Kohring; Maximilian Fichtl; Martin Bichler (CoRR, 2021)

On the Expressiveness of Assignment Messages. - Maximilian Fichtl (CoRR, 2021)

Learning equilibria in symmetric auction games using artificial neural networks. - Martin Bichler; Maximilian Fichtl; Stefan Heidekrüger; Nils Kohring; Paul Sutterer (Nat. Mach. Intell., 2021)

Core-Stability in Assignment Markets with Financially Constrained Buyers. - Eleni Batziou; Martin Bichler; Maximilian Fichtl (EC, 2022)

Computing Candidate Prices in Budget-Constrained Product-Mix Auctions. - Maximilian Fichtl (CoRR, 2022)

Strong substitutes: structural properties, and a new algorithm for competitive equilibrium prices. - Elizabeth Baldwin; Martin Bichler; Maximilian Fichtl; Paul Klemperer (Math. Program., 2024)

Computing Bayes-Nash Equilibrium Strategies in Auction Games via Simultaneous Online Dual Averaging. - Martin Bichler; Maximilian Fichtl; Matthias Oberlechner (Oper. Res., 2025)