Hochreiter, Sepp

98 publications

ICML 2025 A Large Recurrent Action Model: xLSTM Enables Fast Inference for Robotics Tasks Thomas Schmied, Thomas Adler, Vihang Prakash Patil, Maximilian Beck, Korbinian Pöppel, Johannes Brandstetter, Günter Klambauer, Razvan Pascanu, Sepp Hochreiter

ICLRW 2025 Addressing Pitfalls in the Evaluation of Uncertainty Estimation Methods for Natural Language Generation Mykyta Ielanskyi, Kajetan Schweighofer, Lukas Aichberger, Sepp Hochreiter

ICLR 2025 Bio-xLSTM: Generative Modeling, Representation and In-Context Learning of Biological and Chemical Sequences Niklas Schmidinger, Lisa Schneckenreiter, Philipp Seidl, Johannes Schimunek, Pieter-Jan Hoedt, Johannes Brandstetter, Andreas Mayr, Sohvi Luukkonen, Sepp Hochreiter, Günter Klambauer

CVPRW 2025 Comparison Visual Instruction Tuning Wei Lin, Muhammad Jehanzeb Mirza, Sivan Doveh, Rogério Feris, Raja Giryes, Sepp Hochreiter, Leonid Karlinsky

ICLR 2025 FlashRNN: I/O-Aware Optimization of Traditional RNNs on Modern Hardware Korbinian Pöppel, Maximilian Beck, Sepp Hochreiter

ICML 2025 Geometry-Informed Neural Networks Arturs Berzins, Andreas Radler, Eric Volkmann, Sebastian Sanokowski, Sepp Hochreiter, Johannes Brandstetter

ICLRW 2025 Improved Density Ratio Estimation for Evaluating Synthetic Data Quality Lukas Gruber, Markus Holzleitner, Sepp Hochreiter, Werner Zellinger

ICLR 2025 Improving Uncertainty Estimation Through Semantically Diverse Language Generation Lukas Aichberger, Kajetan Schweighofer, Mykyta Ielanskyi, Sepp Hochreiter

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

UAI 2025 On Information-Theoretic Measures of Predictive Uncertainty Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Sepp Hochreiter

NeurIPS 2025 Parameter Efficient Fine-Tuning via Explained Variance Adaptation Fabian Paischer, Lukas Hauzenberger, Thomas Schmied, Benedikt Alkin, Marc Peter Deisenroth, Sepp Hochreiter

NeurIPS 2025 Rethinking Losses for Diffusion Bridge Samplers Sebastian Sanokowski, Lukas Gruber, Christoph Bartmann, Sepp Hochreiter, Sebastian Lehner

ICLRW 2025 Rethinking Uncertainty Estimation in Natural Language Generation Lukas Aichberger, Kajetan Schweighofer, Sepp Hochreiter

ICLRW 2025 Rethinking the Training of Diffusion Bridge Samplers: Losses and Exploration Sebastian Sanokowski, Christoph Bartmann, Lukas Gruber, Sepp Hochreiter, Sebastian Lehner

ICLR 2025 Scalable Discrete Diffusion Samplers: Combinatorial Optimization and Statistical Physics Sebastian Sanokowski, Wilhelm Franz Berghammer, Haoyu Peter Wang, Martin Ennemoser, Sepp Hochreiter, Sebastian Lehner

ICML 2025 The Disparate Benefits of Deep Ensembles Kajetan Schweighofer, Adrian Arnaiz-Rodriguez, Sepp Hochreiter, Nuria M Oliver

NeurIPS 2025 TiRex: Zero-Shot Forecasting Across Long and Short Horizons with Enhanced In-Context Learning Andreas Auer, Patrick Podest, Daniel Klotz, Sebastian Böck, Günter Klambauer, Sepp Hochreiter

NeurIPS 2025 Tiled Flash Linear Attention: More Efficient Linear RNN and xLSTM Kernels Maximilian Beck, Korbinian Pöppel, Phillip Lippe, Sepp Hochreiter

ICLRW 2025 Tiled Flash Linear Attention: More Efficient Linear RNN and xLSTM Kernels Maximilian Beck, Korbinian Pöppel, Phillip Lippe, Sepp Hochreiter

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

NeurIPS 2025 pLSTM: Parallelizable Linear Source Transition Mark Networks Korbinian Pöppel, Richard Freinschlag, Thomas Schmied, Wei Lin, Sepp Hochreiter

ICML 2025 xLSTM 7b: A Recurrent LLM for Fast and Efficient Inference Maximilian Beck, Korbinian Pöppel, Phillip Lippe, Richard Kurle, Patrick M Blies, Günter Klambauer, Sebastian Böck, Sepp Hochreiter

ICLRW 2025 xLSTM 7b: A Recurrent LLM for Fast and Efficient Inference Maximilian Beck, Korbinian Pöppel, Phillip Lippe, Richard Kurle, Patrick M Blies, Günter Klambauer, Sebastian Böck, Sepp Hochreiter

ICML 2024 A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization Sebastian Sanokowski, Sepp Hochreiter, Sebastian Lehner

NeurIPSW 2024 A Large Recurrent Action Model: xLSTM Enables Fast Inference for Robotics Tasks Thomas Schmied, Thomas Adler, Vihang Prakash Patil, Maximilian Beck, Korbinian Pöppel, Johannes Brandstetter, Günter Klambauer, Razvan Pascanu, Sepp Hochreiter

NeurIPSW 2024 Bio-xLSTM: Generative Modeling, Representation and In-Context Learning of Biological and Chemical Sequences Niklas Schmidinger, Lisa Schneckenreiter, Philipp Seidl, Johannes Schimunek, Pieter-Jan Hoedt, Johannes Brandstetter, Andreas Mayr, Sohvi Luukkonen, Sepp Hochreiter, Günter Klambauer

NeurIPSW 2024 Comparison Visual Instruction Tuning Wei Lin, Muhammad Jehanzeb Mirza, Sivan Doveh, Rogerio Feris, Raja Giryes, Sepp Hochreiter, Leonid Karlinsky

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

NeurIPS 2024 Energy-Based Hopfield Boosting for Out-of-Distribution Detection Claus Hofmann, Simon Schmid, Bernhard Lehner, Daniel Klotz, Sepp Hochreiter

ICMLW 2024 Energy-Based Hopfield Boosting for Out-of-Distribution Detection Claus Hofmann, Simon Lucas Schmid, Bernhard Lehner, Daniel Klotz, Sepp Hochreiter

ICMLW 2024 Energy-Based Hopfield Boosting for Out-of-Distribution Detection Claus Hofmann, Simon Lucas Schmid, Bernhard Lehner, Daniel Klotz, Sepp Hochreiter

ICMLW 2024 Geometry-Informed Neural Networks Arturs Berzins, Andreas Radler, Sebastian Sanokowski, Sepp Hochreiter, Johannes Brandstetter

ICLRW 2024 How Many Opinions Does Your LLM Have? Improving Uncertainty Estimation in NLG Lukas Aichberger, Kajetan Schweighofer, Mykyta Ielanskyi, Sepp Hochreiter

NeurIPSW 2024 MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Representations Benedikt Alkin, Lukas Miklautz, Sepp Hochreiter, Johannes Brandstetter

NeurIPSW 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

NeurIPSW 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

ICML 2024 Overcoming Saturation in Density Ratio Estimation by Iterated Regularization Lukas Gruber, Markus Holzleitner, Johannes Lehner, Sepp Hochreiter, Werner Zellinger

ICMLW 2024 Processing Large-Scale Graphs with G-Signatures Lukas Gruber, Bernhard Schäfl, Johannes Brandstetter, Sepp Hochreiter

CoLLAs 2024 Simplified Priors for Object-Centric Learning Vihang Prakash Patil, Andreas Radler, Daniel Klotz, Sepp Hochreiter

CoLLAs 2024 SymbolicAI: A Framework for Logic-Based Approaches Combining Generative Models and Solvers Marius-Constantin Dinu, Claudiu Leoveanu-Condrei, Markus Holzleitner, Werner Zellinger, Sepp Hochreiter

ICMLW 2024 Vision-LSTM: xLSTM as Generic Vision Backbone Benedikt Alkin, Maximilian Beck, Korbinian Pöppel, Sepp Hochreiter, Johannes Brandstetter

NeurIPS 2024 xLSTM: Extended Long Short-Term Memory Maximilian Beck, Korbinian Pöppel, Markus Spanring, Andreas Auer, Oleksandra Prudnikova, Michael Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter

ICMLW 2024 xLSTM: Extended Long Short-Term Memory Maximilian Beck, Korbinian Pöppel, Markus Spanring, Andreas Auer, Oleksandra Prudnikova, Michael K Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter

ICMLW 2024 xLSTM: Extended Long Short-Term Memory Korbinian Pöppel, Maximilian Beck, Markus Spanring, Andreas Auer, Oleksandra Prudnikova, Michael K Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter

ICLR 2023 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 A. Moser, Sergei Pereverzyev, Sepp Hochreiter, Werner Zellinger

AAAI 2023 Boundary Graph Neural Networks for 3D Simulations Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter

NeurIPS 2023 Conformal Prediction for Time Series with Modern Hopfield Networks Andreas Auer, Martin Gauch, Daniel Klotz, Sepp Hochreiter

ICLR 2023 Context-Enriched Molecule Representations Improve Few-Shot Drug Discovery Johannes Schimunek, Philipp Seidl, Lukas Friedrich, Daniel Kuhn, Friedrich Rippmann, Sepp Hochreiter, Günter Klambauer

NeurIPSW 2023 Contrastive Abstraction for Reinforcement Learning Vihang Patil, Markus Hofmarcher, Elisabeth Rumetshofer, Sepp Hochreiter

ICML 2023 Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language Philipp Seidl, Andreu Vall, Sepp Hochreiter, Günter Klambauer

NeurIPSW 2023 Hopfield Boosting for Out-of-Distribution Detection Claus Hofmann, Simon Lucas Schmid, Bernhard Lehner, Daniel Klotz, Sepp Hochreiter

NeurIPSW 2023 Hopular: Modern Hopfield Networks for Tabular Data Bernhard Schäfl, Lukas Gruber, Angela Bitto-Nemling, Sepp Hochreiter

NeurIPSW 2023 Introducing an Improved Information-Theoretic Measure of Predictive Uncertainty Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Sepp Hochreiter

NeurIPSW 2023 Introducing an Improved Information-Theoretic Measure of Predictive Uncertainty Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Sepp Hochreiter

NeurIPS 2023 Learning to Modulate Pre-Trained Models in RL Thomas Schmied, Markus Hofmarcher, Fabian Paischer, Razvan Pascanu, Sepp Hochreiter

ICLRW 2023 Learning to Modulate Pre-Trained Models in RL Thomas Schmied, Markus Hofmarcher, Fabian Paischer, Razvan Pascanu, Sepp Hochreiter

NeurIPSW 2023 Modern Hopfield Networks as Memory for Iterative Learning on Tabular Data Bernhard Schäfl, Lukas Gruber, Angela Bitto-Nemling, Sepp Hochreiter

NeurIPS 2023 Quantification of Uncertainty with Adversarial Models Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Günter Klambauer, Sepp Hochreiter

NeurIPS 2023 Semantic HELM: A Human-Readable Memory for Reinforcement Learning Fabian Paischer, Thomas Adler, Markus Hofmarcher, Sepp Hochreiter

NeurIPSW 2023 VN-EGNN: Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification Florian Sestak, Lisa Schneckenreiter, Sepp Hochreiter, Andreas Mayr, Günter Klambauer

NeurIPSW 2023 VN-EGNN: Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification Florian Sestak, Lisa Schneckenreiter, Sepp Hochreiter, Andreas Mayr, Günter Klambauer

NeurIPS 2023 Variational Annealing on Graphs for Combinatorial Optimization Sebastian Sanokowski, Wilhelm Berghammer, Sepp Hochreiter, Sebastian Lehner

CoLLAs 2022 A Dataset Perspective on Offline Reinforcement Learning Kajetan Schweighofer, Marius-constantin Dinu, Andreas Radler, Markus Hofmarcher, Vihang Prakash Patil, Angela Bitto-nemling, Hamid Eghbal-zadeh, Sepp Hochreiter

ICML 2022 Align-RUDDER: Learning from Few Demonstrations by Reward Redistribution Vihang Patil, Markus Hofmarcher, Marius-Constantin Dinu, Matthias Dorfer, Patrick M Blies, Johannes Brandstetter, José Arjona-Medina, Sepp Hochreiter

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

ICLRW 2022 Contrastive Learning of Image- and Structure-Based Representations in Drug Discovery Ana Sanchez-Fernandez, Elisabeth Rumetshofer, Sepp Hochreiter, Günter Klambauer

CoLLAs 2022 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, Sebastian Lehner

NeurIPSW 2022 Foundation Models for History Compression in Reinforcement Learning Fabian Paischer, Thomas Adler, Andreas Radler, Markus Hofmarcher, Sepp Hochreiter

NeurIPSW 2022 Foundation Models for History Compression in Reinforcement Learning Fabian Paischer, Thomas Adler, Andreas Radler, Markus Hofmarcher, Sepp Hochreiter

ICML 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

NeurIPSW 2022 InfODist: Online Distillation with Informative Rewards Improves Generalization in Curriculum Learning Rahul Siripurapu, Vihang Prakash Patil, Kajetan Schweighofer, Marius-Constantin Dinu, Thomas Schmied, Luis Eduardo Ferro Diez, Markus Holzleitner, Hamid Eghbal-zadeh, Michael K. Kopp, Sepp Hochreiter

NeurIPSW 2022 InfODist: Online Distillation with Informative Rewards Improves Generalization in Curriculum Learning Rahul Siripurapu, Vihang Prakash Patil, Kajetan Schweighofer, Marius-Constantin Dinu, Thomas Schmied, Luis Eduardo Ferro Diez, Markus Holzleitner, Hamid Eghbal-zadeh, Michael K Kopp, Sepp Hochreiter

CoLLAs 2022 Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning Christian Alexander Steinparz, Thomas Schmied, Fabian Paischer, Marius-constantin Dinu, Vihang Prakash Patil, Angela Bitto-nemling, Hamid Eghbal-zadeh, Sepp Hochreiter

NeurIPSW 2022 Robust Task-Specific Adaption of Models for Drug-Target Interaction Prediction Emma Svensson, Pieter-Jan Hoedt, Sepp Hochreiter, Günter Klambauer

NeurIPSW 2022 Toward Semantic History Compression for Reinforcement Learning Fabian Paischer, Thomas Adler, Andreas Radler, Markus Hofmarcher, Sepp Hochreiter

ICLR 2021 Hopfield Networks Is All You Need Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner, Philipp Seidl, Michael Widrich, Lukas Gruber, Markus Holzleitner, Thomas Adler, David Kreil, Michael K Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter

ICML 2021 MC-LSTM: Mass-Conserving LSTM Pieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz, Christina Halmich, Markus Holzleitner, Grey S Nearing, Sepp Hochreiter, Guenter Klambauer

NeurIPSW 2021 Modern Hopfield Networks for Return Decomposition for Delayed Rewards Michael Widrich, Markus Hofmarcher, Vihang Prakash Patil, Angela Bitto-Nemling, Sepp Hochreiter

NeurIPSW 2021 Understanding the Effects of Dataset Characteristics on Offline Reinforcement Learning Kajetan Schweighofer, Markus Hofmarcher, Marius-Constantin Dinu, Philipp Renz, Angela Bitto-Nemling, Vihang Prakash Patil, Sepp Hochreiter

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

NeurIPSW 2019 A GAN Based Solver of Black-Box Inverse Problems Michael Gillhofer, Hubert Ramsauer, Johannes Brandstetter, Bernhard Schäfl, Sepp Hochreiter

ICLR 2019 Human-Level Protein Localization with Convolutional Neural Networks Elisabeth Rumetshofer, Markus Hofmarcher, Clemens Röhrl, Sepp Hochreiter, Günter Klambauer

NeurIPS 2019 RUDDER: Return Decomposition for Delayed Rewards Jose A. Arjona-Medina, Michael Gillhofer, Michael Widrich, Thomas Unterthiner, Johannes Brandstetter, Sepp Hochreiter

ICLR 2018 Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields Thomas Unterthiner, Bernhard Nessler, Calvin Seward, Günter Klambauer, Martin Heusel, Hubert Ramsauer, Sepp Hochreiter

ICML 2018 First Order Generative Adversarial Networks Calvin Seward, Thomas Unterthiner, Urs Bergmann, Nikolay Jetchev, Sepp Hochreiter

NeurIPS 2017 GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, Sepp Hochreiter

NeurIPS 2017 Self-Normalizing Neural Networks Günter Klambauer, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter

ICLR 2016 Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) Djork-Arné Clevert, Thomas Unterthiner, Sepp Hochreiter

NeurIPS 2015 Rectified Factor Networks Djork-Arné Clevert, Andreas Mayr, Thomas Unterthiner, Sepp Hochreiter

NeurIPS 2002 Coulomb Classifiers: Generalizing Support Vector Machines via an Analogy to Electrostatic Systems Sepp Hochreiter, Michael Mozer, Klaus Obermayer

NeurIPS 2002 Feature Selection and Classification on Matrix Data: From Large Margins to Small Covering Numbers Sepp Hochreiter, Klaus Obermayer

NeurIPS 2000 Beyond Maximum Likelihood and Density Estimation: A Sample-Based Criterion for Unsupervised Learning of Complex Models Sepp Hochreiter, Michael Mozer

NeCo 1999 Feature Extraction Through LOCOCODE Sepp Hochreiter, Jürgen Schmidhuber

NeurIPS 1998 Source Separation as a By-Product of Regularization Sepp Hochreiter, Jürgen Schmidhuber

NeCo 1997 Flat Minima Sepp Hochreiter, Jürgen Schmidhuber

NeCo 1997 Long Short-Term Memory Sepp Hochreiter, Jürgen Schmidhuber

NeurIPS 1996 LSTM Can Solve Hard Long Time Lag Problems Sepp Hochreiter, Jürgen Schmidhuber

NeurIPS 1994 Simplifying Neural Nets by Discovering Flat Minima Sepp Hochreiter, Jürgen Schmidhuber