Johannes Brandstetter

89 papers A* 23Journal 62Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Autoregressive deep learning for real-time simulation of soft tissue dynamics during virtual neurosurgery. CoRR Fabian Greifeneder, Wolfgang Fenz, Benedikt Alkin, Johannes Brandstetter, Michael Giretzlehner, Philipp Moser
2026	J	`jnl`	From Circuits to Dynamics: Understanding and Stabilizing Failure in 3D Diffusion Transformers. CoRR Maximilian Plattner, Fabian Paischer, Johannes Brandstetter, Arturs Berzins
2026	J	`jnl`	Stabilizing Test-Time Adaptation of High-Dimensional Simulation Surrogates via D-Optimal Statistics. CoRR Anna Zimmel, Paul Setinek, Gianluca Galletti, Johannes Brandstetter, Werner Zellinger
2026	J	`jnl`	VN-EGNN: E(3)- and SE(3)-Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification. J. Cheminformatics Florian Sestak, Lisa Schneckenreiter, Johannes Brandstetter, Sepp Hochreiter, Andreas Mayr, Günter Klambauer
2026	J	`jnl`	WIND: Weather Inverse Diffusion for Zero-Shot Atmospheric Modeling. CoRR Michael Aich, Andreas Fürst, Florian Sestak, Carlos Ruiz-Gonzalez, Niklas Boers, Johannes Brandstetter
2025	J	`jnl`	5D Neural Surrogates for Nonlinear Gyrokinetic Simulations of Plasma Turbulence. CoRR Gianluca Galletti, Fabian Paischer, Paul Setinek, William Hornsby, Lorenzo Zanisi, Naomi Carey, Stanislas Pamela, Johannes Brandstetter
2025	A*	`conf`	A Large Recurrent Action Model: xLSTM enables Fast Inference for Robotics Tasks. ICML Thomas Schmied, Thomas Adler, Vihang Prakash Patil, Maximilian Beck, Korbinian Pöppel, Johannes Brandstetter, Günter Klambauer, Razvan Pascanu, Sepp Hochreiter
2025	J	`jnl`	A foundation model for the Earth system. Nat. Cristian Bodnar, Wessel P. Bruinsma, Ana Lucic, Megan Stanley, Anna Allen, Johannes Brandstetter, Patrick Garvan, Maik Riechert, Jonathan A. Weyn, Haiyu Dong, Jayesh K. Gupta, Kit Thambiratnam, Alexander T. Archibald, Chun-Chieh Wu, Elizabeth Heider, Max Welling, Richard E. Turner, Paris Perdikaris
2025	J	`jnl`	AB-UPT for Automotive and Aerospace Applications. CoRR Benedikt Alkin, Richard Kurle, Louis Serrano, Dennis Just, Johannes Brandstetter
2025	J	`jnl`	AB-UPT: Scaling Neural CFD Surrogates for High- Fidelity Automotive Aerodynamics Simulations via Anchored- Branched Universal Physics Transformers. Trans. Mach. Learn. Res. Benedikt Alkin, Maurits Bleeker, Richard Kurle, Tobias Kronlachner, Reinhard Sonnleitner, Matthias Dorfer, Johannes Brandstetter
2025	A*	`conf`	Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences. ICLR Niklas Schmidinger, Lisa Schneckenreiter, Philipp Seidl, Johannes Schimunek, Pieter-Jan Hoedt, Johannes Brandstetter, Andreas Mayr, Sohvi Luukkonen, Sepp Hochreiter, Günter Klambauer
2025	J	`jnl`	Einstein Fields: A Neural Perspective To Computational General Relativity. CoRR Sandeep Suresh Cranganore, Andrei Bodnar, Arturs Berzins, Johannes Brandstetter
2025	J	`jnl`	Envisioning better benchmarks for machine learning PDE solvers. Nat. Mac. Intell. Johannes Brandstetter
2025	J	`jnl`	Generative Topology Optimization: Exploring Diverse Solutions in Structural Design. CoRR Andreas Radler, Eric Volkmann, Johannes Brandstetter, Arturs Berzins
2025	A*	`conf`	Geometry-Informed Neural Networks. ICML Arturs Berzins, Andreas Radler, Eric Volkmann, Sebastian Sanokowski, Sepp Hochreiter, Johannes Brandstetter
2025	J	`jnl`	Going with the Speed of Sound: Pushing Neural Surrogates into Highly-turbulent Transonic Regimes. CoRR Fabian Paischer, Léo Cotteleer, Yann Dreze, Richard Kurle, Dylan Rubini, Maurits Bleeker, Tobias Kronlachner, Johannes Brandstetter
2025	J	`jnl`	GyroSwin: 5D Surrogates for Gyrokinetic Plasma Turbulence Simulations. CoRR Fabian Paischer, Gianluca Galletti, William Hornsby, Paul Setinek, Lorenzo Zanisi, Naomi Carey, Stanislas Pamela, Johannes Brandstetter
2025	J	`jnl`	LaM-SLidE: Latent Space Modeling of Spatial Dynamical Systems via Linked Entities. CoRR Florian Sestak, Artur P. Toshev, Andreas Fürst, Günter Klambauer, Andreas Mayr, Johannes Brandstetter
2025	A*	`conf`	MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Masked Image Modeling Representations. ICLR Benedikt Alkin, Lukas Miklautz, Sepp Hochreiter, Johannes Brandstetter
2025	J	`jnl`	Neural surrogates for designing gravitational wave detectors. CoRR Carlos Ruiz-Gonzalez, Sören Arlt, Sebastian Lehner, Arturs Berzins, Yehonathan Drori, Rana X. Adhikari, Johannes Brandstetter, Mario Krenn
2025	J	`jnl`	Neural-Parareal: Self-improving acceleration of fusion MHD simulations using time-parallelisation and neural operators. Comput. Phys. Commun. Stanislas Pamela, Naomi Carey, Johannes Brandstetter, Rob J. Akers, Lorenzo Zanisi, James Buchanan, Vignesh Gopakumar, Matthias Hoelzl, Guido Huijsmans, Kamran Pentland, James Tickner, G. Antonucci
2025	J	`jnl`	NeuralCFD: Deep Learning on High-Fidelity Automotive Aerodynamics Simulations. CoRR Maurits Bleeker, Matthias Dorfer, Tobias Kronlachner, Reinhard Sonnleitner, Benedikt Alkin, Johannes Brandstetter
2025	J	`jnl`	PAINT: Parallel-in-time Neural Twins for Dynamical System Reconstruction. CoRR Andreas Radler, Vincent Seyfried, Stefan Pirker, Johannes Brandstetter, Thomas Lichtenegger
2025	J	`jnl`	SIMSHIFT: A Benchmark for Adapting Neural Surrogates to Distribution Shifts. CoRR Paul Setinek, Gianluca Galletti, Thomas Gross, Dominik Schnürer, Johannes Brandstetter, Werner Zellinger
2025	J	`jnl`	Shape Generation via Weight Space Learning. CoRR Maximilian Plattner, Arturs Berzins, Johannes Brandstetter
2025	J	`jnl`	Towards Multi-Fidelity Scaling Laws of Neural Surrogates in CFD. CoRR Paul Setinek, Gianluca Galletti, Johannes Brandstetter
2025	J	`jnl`	Towards scientific machine learning for granular material simulations - challenges and opportunities. CoRR 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, John Morrissey, Jonathan Nuttall, Jin Y. Ooi, Luisa Orozco, Stefanos-Aldo Papanicolopulos, Tongming Qu, Dingena Schott, Takayuki Shuku, WaiChing Sun, Thomas Weinhart, Dongwei Ye, Hongyang Cheng
2025	A*	`conf`	Vision-LSTM: xLSTM as Generic Vision Backbone. ICLR Benedikt Alkin, Maximilian Beck, Korbinian Pöppel, Sepp Hochreiter, Johannes Brandstetter
2024	J	`jnl`	A Large Recurrent Action Model: xLSTM enables Fast Inference for Robotics Tasks. CoRR Thomas Schmied, Thomas Adler, Vihang Patil, Maximilian Beck, Korbinian Pöppel, Johannes Brandstetter, Günter Klambauer, Razvan Pascanu, Sepp Hochreiter
2024	J	`jnl`	Aurora: A Foundation Model of the Atmosphere. CoRR Cristian Bodnar, Wessel P. Bruinsma, Ana Lucic, Megan Stanley, Johannes Brandstetter, Patrick Garvan, Maik Riechert, Jonathan A. Weyn, Haiyu Dong, Anna Vaughan, Jayesh K. Gupta, Kit Thambiratnam, Alexander T. Archibald, Elizabeth Heider, Max Welling, Richard E. Turner, Paris Perdikaris
2024	J	`jnl`	Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences. CoRR Niklas Schmidinger, Lisa Schneckenreiter, Philipp Seidl, Johannes Schimunek, Pieter-Jan Hoedt, Johannes Brandstetter, Andreas Mayr, Sohvi Luukkonen, Sepp Hochreiter, Günter Klambauer
2024	A*	`conf`	Clifford-Steerable Convolutional Neural Networks. ICML Maksim Zhdanov, David Ruhe, Maurice Weiler, Ana Lucic, Johannes Brandstetter, Patrick Forré
2024	J	`jnl`	Clifford-Steerable Convolutional Neural Networks. CoRR Maksim Zhdanov, David Ruhe, Maurice Weiler, Ana Lucic, Johannes Brandstetter, Patrick Forré
2024	—	`conf`	GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural Networks. Tiny Papers @ ICLR Lisa Schneckenreiter, Richard Freinschlag, Florian Sestak, Johannes Brandstetter, Günter Klambauer, Andreas Mayr
2024	J	`jnl`	GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural Networks. CoRR Lisa Schneckenreiter, Richard Freinschlag, Florian Sestak, Johannes Brandstetter, Günter Klambauer, Andreas Mayr
2024	J	`jnl`	Geometry-Informed Neural Networks. CoRR Arturs Berzins, Andreas Radler, Sebastian Sanokowski, Sepp Hochreiter, Johannes Brandstetter
2024	J	`jnl`	JAX-SPH: A Differentiable Smoothed Particle Hydrodynamics Framework. CoRR Artur P. Toshev, Harish Ramachandran, Jonas A. Erbesdobler, Gianluca Galletti, Johannes Brandstetter, Nikolaus A. Adams
2024	J	`jnl`	MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Representations. CoRR Benedikt Alkin, Lukas Miklautz, Sepp Hochreiter, Johannes Brandstetter
2024	A*	`conf`	Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics. ICML Artur P. Toshev, Jonas A. Erbesdobler, Nikolaus A. Adams, Johannes Brandstetter
2024	J	`jnl`	Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics. CoRR Artur P. Toshev, Jonas A. Erbesdobler, Nikolaus A. Adams, Johannes Brandstetter
2024	J	`jnl`	NeuralDEM - Real-time Simulation of Industrial Particulate Flows. CoRR Benedikt Alkin, Tobias Kronlachner, Samuele Papa, Stefan Pirker, Thomas Lichtenegger, Johannes Brandstetter
2024	J	`jnl`	Universal Physics Transformers. CoRR Benedikt Alkin, Andreas Fürst, Simon Schmid, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter
2024	A*	`conf`	Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators. NeurIPS Benedikt Alkin, Andreas Fürst, Simon Schmid, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter
2024	J	`jnl`	VN-EGNN: E(3)-Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification. CoRR Florian Sestak, Lisa Schneckenreiter, Johannes Brandstetter, Sepp Hochreiter, Andreas Mayr, Günter Klambauer
2024	J	`jnl`	Vision-LSTM: xLSTM as Generic Vision Backbone. CoRR Benedikt Alkin, Maximilian Beck, Korbinian Pöppel, Sepp Hochreiter, Johannes Brandstetter
2024	A*	`conf`	xLSTM: Extended Long Short-Term Memory. NeurIPS Maximilian Beck, Korbinian Pöppel, Markus Spanring, Andreas Auer, Oleksandra Prudnikova, Michael Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter
2024	J	`jnl`	xLSTM: Extended Long Short-Term Memory. CoRR Maximilian Beck, Korbinian Pöppel, Markus Spanring, Andreas Auer, Oleksandra Prudnikova, Michael Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter
2023	A*	`conf`	Boundary Graph Neural Networks for 3D Simulations. AAAI Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter
2023	A*	`conf`	Clifford Group Equivariant Neural Networks. NeurIPS David Ruhe, Johannes Brandstetter, Patrick Forré
2023	J	`jnl`	Clifford Group Equivariant Neural Networks. CoRR David Ruhe, Johannes Brandstetter, Patrick Forré
2023	A*	`conf`	Clifford Neural Layers for PDE Modeling. ICLR Johannes Brandstetter, Rianne van den Berg, Max Welling, Jayesh K. Gupta
2023	A*	`conf`	ClimaX: A foundation model for weather and climate. ICML Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K. Gupta, Aditya Grover
2023	J	`jnl`	ClimaX: A foundation model for weather and climate. CoRR Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K. Gupta, Aditya Grover
2023	J	`jnl`	E(3) Equivariant Graph Neural Networks for Particle-Based Fluid Mechanics. CoRR Artur P. Toshev, Gianluca Galletti, Johannes Brandstetter, Stefan Adami, Nikolaus A. Adams
2023	J	`jnl`	G-Signatures: Global Graph Propagation With Randomized Signatures. CoRR Bernhard Schäfl, Lukas Gruber, Johannes Brandstetter, Sepp Hochreiter
2023	A*	`conf`	Geometric Clifford Algebra Networks. ICML David Ruhe, Jayesh K. Gupta, Steven De Keninck, Max Welling, Johannes Brandstetter
2023	J	`jnl`	Geometric Clifford Algebra Networks. CoRR David Ruhe, Jayesh K. Gupta, Steven De Keninck, Max Welling, Johannes Brandstetter
2023	J	`jnl`	Learning Lagrangian Fluid Mechanics with E(3)-Equivariant Graph Neural Networks. CoRR Artur P. Toshev, Gianluca Galletti, Johannes Brandstetter, Stefan Adami, Nikolaus A. Adams
2023	J	`jnl`	Lie Point Symmetry and Physics Informed Networks. CoRR Tara Akhound-Sadegh, Laurence Perreault Levasseur, Johannes Brandstetter, Max Welling, Siamak Ravanbakhsh
2023	A*	`conf`	Lie Point Symmetry and Physics-Informed Networks. NeurIPS Tara Akhound-Sadegh, Laurence Perreault Levasseur, Johannes Brandstetter, Max Welling, Siamak Ravanbakhsh
2023	A*	`conf`	PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers. NeurIPS Phillip Lippe, Bas Veeling, Paris Perdikaris, Richard E. Turner, Johannes Brandstetter
2023	J	`jnl`	PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers. CoRR Phillip Lippe, Bastiaan S. Veeling, Paris Perdikaris, Richard E. Turner, Johannes Brandstetter
2023	J	`jnl`	Towards Multi-spatiotemporal-scale Generalized PDE Modeling. Trans. Mach. Learn. Res. Jayesh K. Gupta, Johannes Brandstetter
2022	A*	`conf`	Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution. ICML Vihang Patil, Markus Hofmarcher, Marius-Constantin Dinu, Matthias Dorfer, Patrick M. Blies, Johannes Brandstetter, José Antonio Arjona-Medina, Sepp Hochreiter
2022	J	`jnl`	Clifford Neural Layers for PDE Modeling. CoRR Johannes Brandstetter, Rianne van den Berg, Max Welling, Jayesh K. Gupta
2022	—	`conf`	Few-Shot Learning by Dimensionality Reduction in Gradient Space. CoLLAs 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
2022	J	`jnl`	Few-Shot Learning by Dimensionality Reduction in Gradient Space. CoRR 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
2022	A*	`conf`	Geometric and Physical Quantities improve E(3) Equivariant Message Passing. ICLR Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik J. Bekkers, Max Welling
2022	A*	`conf`	Lie Point Symmetry Data Augmentation for Neural PDE Solvers. ICML Johannes Brandstetter, Max Welling, Daniel E. Worrall
2022	J	`jnl`	Lie Point Symmetry Data Augmentation for Neural PDE Solvers. CoRR Johannes Brandstetter, Max Welling, Daniel E. Worrall
2022	A*	`conf`	Message Passing Neural PDE Solvers. ICLR Johannes Brandstetter, Daniel E. Worrall, Max Welling
2022	J	`jnl`	Message Passing Neural PDE Solvers. CoRR Johannes Brandstetter, Daniel E. Worrall, Max Welling
2022	J	`jnl`	Towards Multi-spatiotemporal-scale Generalized PDE Modeling. CoRR Jayesh K. Gupta, Johannes Brandstetter
2021	J	`jnl`	Boundary Graph Neural Networks for 3D Simulations. CoRR Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter
2021	J	`jnl`	Convergence Proof for Actor-Critic Methods Applied to PPO and RUDDER. Trans. Large Scale Data Knowl. Centered Syst. Markus Holzleitner, Lukas Gruber, José Antonio Arjona-Medina, Johannes Brandstetter, Sepp Hochreiter
2021	J	`jnl`	Geometric and Physical Quantities improve E(3) Equivariant Message Passing. CoRR Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik J. Bekkers, Max Welling
2021	A*	`conf`	Hopfield Networks is All You Need. ICLR Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner, Philipp Seidl, Michael Widrich, Lukas Gruber, Markus Holzleitner, Thomas Adler, David P. Kreil, Michael K. Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter
2021	J	`jnl`	Learning 3D Granular Flow Simulations. CoRR Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter
2021	—	`conf`	Learning Lagrangian Fluid Mechanics with E(3)-Equivariant Graph Neural Networks. GSI (2) Artur P. Toshev, Gianluca Galletti, Johannes Brandstetter, Stefan Adami, Nikolaus A. Adams
2020	J	`jnl`	Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution. CoRR Vihang Prakash Patil, Markus Hofmarcher, Marius-Constantin Dinu, Matthias Dorfer, Patrick M. Blies, Johannes Brandstetter, Jose A. Arjona-Medina, Sepp Hochreiter
2020	J	`jnl`	Convergence Proof for Actor-Critic Methods Applied to PPO and RUDDER. CoRR Markus Holzleitner, Lukas Gruber, Jose A. Arjona-Medina, Johannes Brandstetter, Sepp Hochreiter
2020	J	`jnl`	Cross-Domain Few-Shot Learning by Representation Fusion. CoRR Thomas Adler, Johannes Brandstetter, Michael Widrich, Andreas Mayr, David P. Kreil, Michael Kopp, Günter Klambauer, Sepp Hochreiter
2020	J	`jnl`	Hopfield Networks is All You Need. CoRR 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, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter
2020	A*	`conf`	Modern Hopfield Networks and Attention for Immune Repertoire Classification. NeurIPS Michael Widrich, Bernhard Schäfl, Milena Pavlovic, Hubert Ramsauer, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter, Geir Kjetil Sandve, Victor Greiff, Sepp Hochreiter, Günter Klambauer
2020	J	`jnl`	Modern Hopfield Networks and Attention for Immune Repertoire Classification. CoRR Michael Widrich, Bernhard Schäfl, Hubert Ramsauer, Milena Pavlovic, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter, Geir Kjetil Sandve, Victor Greiff, Sepp Hochreiter, Günter Klambauer
2020	—	`conf`	XAI and Strategy Extraction via Reward Redistribution. xxAI@ICML Marius-Constantin Dinu, Markus Hofmarcher, Vihang Prakash Patil, Matthias Dorfer, Patrick M. Blies, Johannes Brandstetter, Jose A. Arjona-Medina, Sepp Hochreiter
2019	J	`jnl`	Quantum Optical Experiments Modeled by Long Short-Term Memory. CoRR Thomas Adler, Manuel Erhard, Mario Krenn, Johannes Brandstetter, Johannes Kofler, Sepp Hochreiter
2019	A*	`conf`	RUDDER: Return Decomposition for Delayed Rewards. NeurIPS Jose A. Arjona-Medina, Michael Gillhofer, Michael Widrich, Thomas Unterthiner, Johannes Brandstetter, Sepp Hochreiter
2019	J	`jnl`	Using LSTMs for climate change assessment studies on droughts and floods. CoRR Frederik Kratzert, Daniel Klotz, Johannes Brandstetter, Pieter-Jan Hoedt, Grey Nearing, Sepp Hochreiter