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)

MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Representations. - Benedikt Alkin; Lukas Miklautz; Sepp Hochreiter; Johannes Brandstetter (CoRR, 2024)

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

One Initialization to Rule them All: Fine-tuning via Explained Variance Adaptation. - Fabian Paischer; Lukas Hauzenberger; Thomas Schmied; Benedikt Alkin; Marc Peter Deisenroth; Sepp Hochreiter (CoRR, 2024)

NeuralDEM - Real-time Simulation of Industrial Particulate Flows. - Benedikt Alkin; Tobias Kronlachner; Samuele Papa; Stefan Pirker; Thomas Lichtenegger; Johannes Brandstetter (CoRR, 2024)

Vision-LSTM: xLSTM as Generic Vision Backbone. - Benedikt Alkin; Maximilian Beck; Korbinian Pöppel; Sepp Hochreiter; Johannes Brandstetter (ICLR, 2025)

MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Masked Image Modeling Representations. - Benedikt Alkin; Lukas Miklautz; Sepp Hochreiter; Johannes Brandstetter (ICLR, 2025)

NeuralCFD: Deep Learning on High-Fidelity Automotive Aerodynamics Simulations. - Maurits Bleeker; Matthias Dorfer; Tobias Kronlachner; Reinhard Sonnleitner; Benedikt Alkin; 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)