Improving Clinical Predictions with Multi-Modal Pre-training in Retinal Imaging

Author(s):	Emese Sükei, Elisabeth Rumetshofer, Niklas Schmidinger, Andreas Mayr, Ursula Schmidt-Erfurth, Günter Klambauer, Hrvoje Bogunović
Published:	In 2024 IEEE International Symposium on Biomedical Imaging (ISBI) (pp. 1-5) https://doi.org/10.1109/ISBI56570.2024.10635447, opens an external URL in a new window

Enriching AI-based Predictive Models from Retinal Imaging by Multi-Modal Contrastive Pre-training

Author(s):	Emese Sükei, Sophie Riedl, Elisabeth Rumetshofer, Niklas Schmidinger, Andreas Mayr, Ursula Schmidt-Erfurth, Günter Klambauer, Hrvoje Bogunovic
Published:	Investigative Ophthalmology & Visual Science, 65(7), pp 450-450, 2024

A data-centric perspective on the information needed for hydrological uncertainty predictions

Author(s):	Andreas Auer, Martin Gauch, Frederik Kratzert, Grey Nearing, Sepp Hochreiter, and Daniel Klotz
Published:	Hydrology and Earth System Sciences Discussions, 28(17), pp 4099–4126, 2024 https://doi.org/10.5194/hess-28-4099-2024, opens an external URL in a new window

A community effort in SARS-CoV-2 drug discovery

Author(s):	Johannes Schimunek, Philipp Seidl, Katarina Elez, Tim Hempel, Tuan Le, Frank Noé, Simon Olsson, Lluís Raich, Robin Winter, Hatice Gokcan, and others
Published:	Molecular Informatics, 2024, Vol. 43(1), pp. e202300262

HyperPCM: Robust Task-Conditioned Modeling of Drug−Target Interactions

Author(s):	Emma Svensson, Pieter-Jan Hoedt, Sepp Hochreiter, and Günter Klambauer
Published:	Journal of Chemical Information and Modeling, American Chemical Society, 2024

Potential Predictors for Deterioration of Renal Function After Transfusion

Author(s):	Thomas Tschoellitsch , Philipp Moser, Alexander Maletzky, Philipp Seidl, Carl Böck, Theresa Roland, Helga Ludwig, Susanne Süssner, Sepp Hochreiter, Jens Meier
Published:	Anesthesia & Analgesia, LWW, 2024, Vol. 138(3), pp. 645-654 http://dx.doi.org/10.1213/ANE.0000000000006720, opens an external URL in a new window

MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Representations

Author(s):	Benedikt Alkin, Andreas Fürst, Simon Schmid, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter
Published:	Conference Neural Information Processing Systems Foundation (NeurIPS 2024), Poster Presentation, December 09 - December 15, 2024, Vancouver, Canada PDF, opens an external URL in a new window

Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators

Author(s):	Benedikt Alkin, Andreas Fürst, Simon Schmid, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter
Published:	Conference Neural Information Processing Systems Foundation (NeurIPS 2024), Poster Presentation, December 09 - December 15, 2024, Vancouver, Canada PDF, opens an external URL in a new window

Meta-Prompting for Automating Zero-shot Visual Recognition with LLMs

Author(s):	M. Jehanzeb Mirza, Leonid Karlinsky, Wei Lin, Sivan Doveh, Jakub Micorek, Mateusz Kozinski, Hilde Kuehne, Horst Possegger
Published:	The 18th European Conference on Computer Vision ECCV 2024 https://doi.org/10.48550/arXiv.2403.11755, opens an external URL in a new window

Clifford-Steerable Convolutional Neural Networks

Author(s):	Maksim Zhdanov, David Ruhe, Maurice Weiler, Ana Lucic, Johannes Brandstetter, Patrick Forré
Published:	International Conference on Machine Learning (ICML 2024), Jul 21-27, 2024, Vienna, Austria Proceedings, opens an external URL in a new window, https://arxiv.org/abs/2402.14730, opens an external URL in a new window

Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics

Author(s):	Artur Toshev, Jonas Erbesdobler, Nikolaus Adams, Johannes Brandstetter
Published:	International Conference on Machine Learning (ICML 2024), Jul 21-27,2024, Vienna, Austria Proceedings, opens an external URL in a new window, https://arxiv.org/abs/2402.06275, opens an external URL in a new window

A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization

Author(s):	Sebastian Sanokowski, Sepp Hochreiter, Sebastian Lehner
Published:	International Conference on Machine Learning (ICML 2024), Jul 21-27,2024, Vienna, Austria Proceedings, opens an external URL in a new window, https://arxiv.org/abs/2406.01661, opens an external URL in a new window, https://arxiv.org/abs/2402.13891, opens an external URL in a new window

Overcoming Saturation in Density Ratio Estimation by Iterated Regularization

Author(s):	Lukas Gruber, Markus Holzleitner, Johannes Lehner, Sepp Hochreiter, Werner Zellinger
Published:	International Conference on Machine Learning (ICML 2024), Jul 21-27,2024, Vienna, Austria Proceedings, opens an external URL in a new window,

Incorporating probabilistic domain knowledge into deep multiple instance learning

Author(s):	Ghadi S. Al Hajj, Aliaksandr Hubin, Chakravarthi Kanduri, Milena Pavlović, Knut Rand, Michael Widrich, Anne Solberg, Victor Greiff, Johan Pensar, Günter Klambauer, Geir Kjetil Sandve
Published:	International Conference on Machine Learning (ICML 2024), Jul 21-27,2024, Vienna, Austria Proceedings, opens an external URL in a new window

Geometry-informed Neural Networks

Author(s):	Arturs Berzins, Andreas Radler, Sebastian Sanokowski, Sepp Hochreiter, Johannes Brandstetter
Published:	International Conference on Machine Learning (ICML 2024), Workshop on Geometry-grounded Representation Learning and Generative Modeling, Jul 21-27,2024, Vienna, Austria Paper, opens an external URL in a new window

Energy-based Hopfield Boosting for Out-of-Distribution Detection

Author(s):	Claus Hofmann, Simon Lucas Schmid, Bernhard Lehner, Daniel Klotz, Sepp Hochreiter
Published:	International Conference on Machine Learning (ICML 2024), Workshop on Geometry-grounded Representation Learning and Generative Modeling, Jul 21-27,2024, Vienna, Austria Workshop Paper, opens an external URL in a new window

Contrastive tuning: A little help to make masked autoencoders forget

Author(s):	Johannes Lehner, Benedikt Alkin, Andreas Fürst, Elisabeth Rumetshofer, Lukas Miklautz, Sepp Hochreiter
Published:	Proceedings of the AAAI Conference on Artificial Intelligence, 2024, Vol. 38(4), pp.2965-2973

NeuralDEM - Real-time Simulation of Industrial Particulate Flows

Author(s):	Benedikt Alkin, Tobias Kronlachner, Samuele Papa, Stefan Pirker, Thomas Lichtenegger, Johannes Brandstetter
Published:	arXiv.2411.09678, opens an external URL in a new window

Large Language Models Can Self-Improve At Web Agent Tasks

Author(s):	Ajay Patel, Markus Hofmarcher, Claudiu Leoveanu-Condrei, Marius-Constantin Dinu, Chris Callison-Burch, Sepp Hochreiter
Published:	arXiv:2405.20309, opens an external URL in a new window

Vision-LSTM: xLSTM as Generic Vision Backbone

Author(s):	Benedikt Alkin, Maximilian Beck, Korbinian Pöppel, Sepp Hochreiter, Johannes Brandstetter
Published:	arXiv:2406.04303, opens an external URL in a new window

Comparison Visual Instruction Tuning

Author(s):	Wei Lin, Muhammad Jehanzeb Mirza, Sivan Doveh, Rogerio Feris, Raja Giryes, Sepp Hochreiter, Leonid Karlinsky
Published:	arXiv:2406.09240, opens an external URL in a new window

Energy-based Hopfield Boosting for Out-of-Distribution Detection

Author(s):	Claus Hofmann, Simon Schmid, Bernhard Lehner, Daniel Klotz, Sepp Hochreiter
Published:	arXiv:2405.08766, opens an external URL in a new window

Semantically Diverse Language Generation for Uncertainty Estimation in Language Models

Author(s):	Lukas Aichberger, Kajetan Schweighofer, Mykyta Ielanskyi, Sepp Hochreiter
Published:	arXiv:2406.04306, opens an external URL in a new window

xLSTM: Extended Long Short-Term Memory

Author(s):	Maximilian Beck, Korbinian Pöppel, Markus Spanring, Andreas Auer, Oleksandra Prudnikova, Michael Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter
Published:	arXiv:2405.04517 , opens an external URL in a new window

VN-EGNN: E(3)-Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification

Author(s):	Florian Sestak, Lisa Schneckenreiter, Johannes Brandstetter, Sepp Hochreiter, Andreas Mayr, Günter Klambauer
Published:	arXiv:2404.07194 , opens an external URL in a new window

Geometry-Informed Neural Networks

Author(s):	Arturs Berzins, Andreas Radler, Sebastian Sanokowski, Sepp Hochreiter, Johannes Brandstetter
Published:	arXiv:2402.14009 , opens an external URL in a new window

Overcoming Saturation in Density Ratio Estimation by Iterated Regularization

Author(s):	Lukas Gruber, Markus Holzleitner, Johannes Lehner, Sepp Hochreiter, Werner Zellinger
Published:	arXiv:2402.13891 , opens an external URL in a new window

MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Representations

Author(s):	Benedikt Alkin, Lukas Miklautz, Sepp Hochreiter, Johannes Brandstetter
Published:	arXiv:2402.10093, opens an external URL in a new window

SymbolicAI: A framework for logic-based approaches combining generative models and solvers

Author(s):	Marius-Constantin Dinu, Claudiu Leoveanu-Condrei, Markus Holzleitner, Werner Zellinger, Sepp Hochreiter
Published:	arXiv:2402.00854, opens an external URL in a new window

Introducing an Improved Information-Theoretic Measure of Predictive Uncertainty

Author(s):	Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Sepp Hochreiter
Published:	arXiv:2311.08309, opens an external URL in a new window

Linear Alignment of Vision-language Models for Image Captioning

Author(s):	Fabian Paischer, Markus Hofmarcher, Sepp Hochreiter, Thomas Adler
Published:	arXiv:2307.05591, opens an external URL in a new window

Contrastive Abstraction for Reinforcement Learning

Author(s):	Vihang Patil, Markus Hofmarcher, Elisabeth Rumetshofer, Sepp Hochreiter
Published:	arXiv.2410.00704, opens an external URL in a new window

NeuralDEM -- Real-time Simulation of Industrial Particulate Flows

Author(s):	Benedikt Alkin, Tobias Kronlachner, Samuele Papa, Stefan Pirker, Thomas Lichtenegger, Johannes Brandstetter
Published:	arXiv.2411.09678, opens an external URL in a new window