Modern Hopfield Networks and Attention for Immune Repertoire Classification. - Michael Widrich; Bernhard Schäfl; Milena Pavlovic; Hubert Ramsauer; Lukas Gruber; Markus Holzleitner; Johannes Brandstetter; Geir Kjetil Sandve; Victor Greiff; Sepp Hochreiter; Günter Klambauer (NeurIPS, 2020)

Hopfield Networks is All You Need. - Hubert Ramsauer; Bernhard Schäfl; Johannes Lehner; Philipp Seidl; Michael Widrich; Lukas Gruber; Markus Holzleitner; Milena Pavlovic; Geir Kjetil Sandve; Victor Greiff; David P. Kreil; Michael Kopp 001; et al. (CoRR, 2020)

Hopfield Networks is All You Need. - Hubert Ramsauer; Bernhard Schäfl; Johannes Lehner; Philipp Seidl; Michael Widrich; Lukas Gruber; Markus Holzleitner; Thomas Adler; David P. Kreil; Michael K. Kopp 001; Günter Klambauer; Johannes Brandstetter; et al. (ICLR, 2021)

MC-LSTM: Mass-Conserving LSTM. - Pieter-Jan Hoedt; Frederik Kratzert; Daniel Klotz; Christina Halmich; Markus Holzleitner; Grey Nearing; Sepp Hochreiter; Günter Klambauer (ICML, 2021)

Convergence Proof for Actor-Critic Methods Applied to PPO and RUDDER. - Markus Holzleitner; Lukas Gruber; José Antonio Arjona-Medina; Johannes Brandstetter; Sepp Hochreiter (Trans. Large Scale Data Knowl. Centered Syst., 2021)

Few-Shot Learning by Dimensionality Reduction in Gradient Space. - Martin Gauch; Maximilian Beck; Thomas Adler; Dmytro Kotsur; Stefan Fiel; Hamid Eghbal-zadeh; Johannes Brandstetter; Johannes Kofler; Markus Holzleitner; Werner Zellinger; Daniel Klotz; Sepp Hochreiter; et al. (CoLLAs, 2022)

History Compression via Language Models in Reinforcement Learning. - Fabian Paischer; Thomas Adler; Vihang Patil; Angela Bitto-Nemling; Markus Holzleitner; Sebastian Lehner; Hamid Eghbal-Zadeh; Sepp Hochreiter (ICML, 2022)

Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation. - Marius-Constantin Dinu; Markus Holzleitner; Maximilian Beck; Hoan Duc Nguyen; Andrea Huber; Hamid Eghbal-zadeh; Bernhard Alois Moser; Sergei V. Pereverzyev; Sepp Hochreiter; Werner Zellinger (ICLR, 2023)

Domain Generalization by Functional Regression. - Markus Holzleitner; Sergei V. Pereverzyev; Werner Zellinger (CoRR, 2023)

SymbolicAI: A framework for logic-based approaches combining generative models and solvers. - Marius-Constantin Dinu; Claudiu Leoveanu-Condrei; Markus Holzleitner; Werner Zellinger; Sepp Hochreiter (CoLLAs, 2024)

Overcoming Saturation in Density Ratio Estimation by Iterated Regularization. - Lukas Gruber; Markus Holzleitner; Johannes Lehner; Sepp Hochreiter; Werner Zellinger (ICML, 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)

Multiparameter regularization and aggregation in the context of polynomial functional regression. - Elke Ruth Gizewski; Markus Holzleitner; Lukas Mayer-Suess; Sergiy Pereverzyev Jr.; Sergei V. Pereverzyev (CoRR, 2024)

On regularized polynomial functional regression. - Markus Holzleitner; Sergei V. Pereverzyev (J. Complex., 2024)