Robustness certification with generative models. - Matthew Mirman; Alexander Hägele; Pavol Bielik; Timon Gehr; Martin T. Vechev (PLDI, 2021)

BaCaDI: Bayesian Causal Discovery with Unknown Interventions. - Alexander Hägele; Jonas Rothfuss; Lars Lorch; Vignesh Ram Somnath; Bernhard Schölkopf; Andreas Krause 001 (AISTATS, 2023)

Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations. - Alexander Hägele; Elie Bakouch; Atli Kosson; Loubna Ben Allal; Leandro von Werra; Martin Jaggi (NeurIPS, 2024)

The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training. - Fabian Schaipp; Alexander Hägele; Adrien B. Taylor; Umut Simsekli; Francis R. Bach (CoRR, 2025)

Inverse Scaling in Test-Time Compute. - Aryo Pradipta Gema; Alexander Hägele; Runjin Chen; Andy Arditi; Jacob Goldman-Wetzler; Kit Fraser-Taliente; Henry Sleight; Linda Petrini; Julian Michael; Beatrice Alex; Pasquale Minervini; Yanda Chen; et al. (CoRR, 2025)