Abstract Data Types in Event-B - An Application of Generic Instantiation - David A. Basin; Andreas Fürst; Thai Son Hoang; Kunihiko Miyazaki; Naoto Sato (CoRR, 2012)

Event-B patterns and their tool support. - Thai Son Hoang; Andreas Fürst; Jean-Raymond Abrial (Softw. Syst. Model., 2013)

Formal System Modelling Using Abstract Data Types in Event-B. - Andreas Fürst; Thai Son Hoang; David A. Basin; Naoto Sato; Kunihiko Miyazaki (ABZ, 2014)

Code Generation for Event-B. - Andreas Fürst; Thai Son Hoang; David A. Basin; Krishnaji Desai; Naoto Sato; Kunihiko Miyazaki (IFM, 2014)

Formal development of a train control system using Event-B. - Andreas Fürst (2015)

Large-scale system development using Abstract Data Types and refinement. - Andreas Fürst; Thai Son Hoang; David A. Basin; Naoto Sato; Kunihiko Miyazaki (Sci. Comput. Program., 2016)

CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP. - Andreas Fürst; Elisabeth Rumetshofer; Viet Tran; Hubert Ramsauer; Fei Tang; Johannes Lehner; David P. Kreil; Michael Kopp 001; Günter Klambauer; Angela Bitto-Nemling; Sepp Hochreiter (CoRR, 2021)

CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP. - Andreas Fürst; Elisabeth Rumetshofer; Johannes Lehner; Viet T. Tran; Fei Tang; Hubert Ramsauer; David P. Kreil; Michael Kopp 001; Günter Klambauer; Angela Bitto; Sepp Hochreiter (NeurIPS, 2022)

Contrastive Tuning: A Little Help to Make Masked Autoencoders Forget. - Johannes Lehner; Benedikt Alkin; Andreas Fürst; Elisabeth Rumetshofer; Lukas Miklautz; Sepp Hochreiter (AAAI, 2024)

Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators. - Benedikt Alkin; Andreas Fürst; Simon Schmid; Lukas Gruber; Markus Holzleitner; Johannes Brandstetter (NeurIPS, 2024)

Universal Physics Transformers. - Benedikt Alkin; Andreas Fürst; Simon Schmid; Lukas Gruber; Markus Holzleitner; Johannes Brandstetter (CoRR, 2024)

LaM-SLidE: Latent Space Modeling of Spatial Dynamical Systems via Linked Entities. - Florian Sestak; Artur P. Toshev; Andreas Fürst; Günter Klambauer; Andreas Mayr; Johannes Brandstetter (CoRR, 2025)

Towards scientific machine learning for granular material simulations - challenges and opportunities. - Marc Fransen; Andreas Fürst; Deepak Tunuguntla; Daniel N. Wilke; Benedikt Alkin; Daniel Barreto; Johannes Brandstetter; Miguel Angel Cabrera; Xinyan Fan; Mengwu Guo; Bram Kieskamp; Krishna Kumar; et al. (CoRR, 2025)