Johannes Brandstetter

According to our database, Johannes Brandstetter authored at least 67 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

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

Florian Sestak, Lisa Schneckenreiter, Johannes Brandstetter, Sepp Hochreiter, Andreas Mayr, Günter Klambauer

J. Cheminformatics, December, 2026

ANTIC: Adaptive Neural Temporal In-situ Compressor.

Sandeep Suresh Cranganore, Andrei Bodnar, Gianluca Galleti, Fabian Paischer, Johannes Brandstetter

CoRR, April, 2026

Stabilizing Test-Time Adaptation of High-Dimensional Simulation Surrogates via D-Optimal Statistics.

Anna Zimmel, Paul Setinek, Gianluca Galletti, Johannes Brandstetter, Werner Zellinger

CoRR, February, 2026

From Circuits to Dynamics: Understanding and Stabilizing Failure in 3D Diffusion Transformers.

Maximilian Plattner, Fabian Paischer, Johannes Brandstetter, Arturs Berzins

CoRR, February, 2026

WIND: Weather Inverse Diffusion for Zero-Shot Atmospheric Modeling.

Michael Aich, Andreas Fürst, Florian Sestak, Carlos Ruiz-Gonzalez, Niklas Boers, Johannes Brandstetter

CoRR, February, 2026

Autoregressive deep learning for real-time simulation of soft tissue dynamics during virtual neurosurgery.

Fabian Greifeneder, Wolfgang Fenz, Benedikt Alkin, Johannes Brandstetter, Michael Giretzlehner, Philipp Moser

CoRR, January, 2026

2025

Going with the Speed of Sound: Pushing Neural Surrogates into Highly-turbulent Transonic Regimes.

Fabian Paischer, Léo Cotteleer, Yann Dreze, Richard Kurle, Dylan Rubini, Maurits Bleeker, Tobias Kronlachner, Johannes Brandstetter

CoRR, November, 2025

Neural surrogates for designing gravitational wave detectors.

Carlos Ruiz-Gonzalez, Sören Arlt, Sebastian Lehner, Arturs Berzins, Yehonathan Drori, Rana X. Adhikari, Johannes Brandstetter, Mario Krenn

CoRR, November, 2025

Towards Multi-Fidelity Scaling Laws of Neural Surrogates in CFD.

Paul Setinek, Gianluca Galletti, Johannes Brandstetter

CoRR, November, 2025

PAINT: Parallel-in-time Neural Twins for Dynamical System Reconstruction.

Andreas Radler, Vincent Seyfried, Stefan Pirker, Johannes Brandstetter, Thomas Lichtenegger

CoRR, October, 2025

AB-UPT for Automotive and Aerospace Applications.

Benedikt Alkin, Richard Kurle, Louis Serrano, Dennis Just, Johannes Brandstetter

CoRR, October, 2025

GyroSwin: 5D Surrogates for Gyrokinetic Plasma Turbulence Simulations.

Fabian Paischer, Gianluca Galletti, William Hornsby, Paul Setinek, Lorenzo Zanisi, Naomi Carey, Stanislas Pamela, Johannes Brandstetter

CoRR, October, 2025

Einstein Fields: A Neural Perspective To Computational General Relativity.

Sandeep Suresh Cranganore, Andrei Bodnar, Arturs Berzins, Johannes Brandstetter

CoRR, July, 2025

SIMSHIFT: A Benchmark for Adapting Neural Surrogates to Distribution Shifts.

Paul Setinek, Gianluca Galletti, Thomas Gross, Dominik Schnürer, Johannes Brandstetter, Werner Zellinger

CoRR, June, 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, 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

CoRR, April, 2025

Shape Generation via Weight Space Learning.

Maximilian Plattner, Arturs Berzins, Johannes Brandstetter

CoRR, March, 2025

Generative Topology Optimization: Exploring Diverse Solutions in Structural Design.

Andreas Radler, Eric Volkmann, Johannes Brandstetter, Arturs Berzins

CoRR, February, 2025

NeuralCFD: Deep Learning on High-Fidelity Automotive Aerodynamics Simulations.

Maurits Bleeker, Matthias Dorfer, Tobias Kronlachner, Reinhard Sonnleitner, Benedikt Alkin, Johannes Brandstetter

CoRR, February, 2025

5D Neural Surrogates for Nonlinear Gyrokinetic Simulations of Plasma Turbulence.

Gianluca Galletti, Fabian Paischer, Paul Setinek, William Hornsby, Lorenzo Zanisi, Naomi Carey, Stanislas Pamela, Johannes Brandstetter

CoRR, February, 2025

AB-UPT: Scaling Neural CFD Surrogates for High- Fidelity Automotive Aerodynamics Simulations via Anchored- Branched Universal Physics Transformers.

Benedikt Alkin, Maurits Bleeker, Richard Kurle, Tobias Kronlachner, Reinhard Sonnleitner, Matthias Dorfer, Johannes Brandstetter

Trans. Mach. Learn. Res., 2025

A foundation model for the Earth system.

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

Nat., 2025

Envisioning better benchmarks for machine learning PDE solvers.

Johannes Brandstetter

Nat. Mac. Intell., 2025

Neural-Parareal: Self-improving acceleration of fusion MHD simulations using time-parallelisation and neural operators.

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

Comput. Phys. Commun., 2025

LaM-SLidE: Latent Space Modeling of Spatial Dynamical Systems via Linked Entities.

Florian Sestak, Artur P. Toshev, Andreas Fürst, Günter Klambauer, Andreas Mayr, Johannes Brandstetter

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 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

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Geometry-Informed Neural Networks.

Arturs Berzins, Andreas Radler, Eric Volkmann, Sebastian Sanokowski, Sepp Hochreiter, Johannes Brandstetter

Proceedings of the Forty-second International Conference on Machine Learning, 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

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Masked Image Modeling Representations.

Benedikt Alkin, Lukas Miklautz, Sepp Hochreiter, Johannes Brandstetter

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Vision-LSTM: xLSTM as Generic Vision Backbone.

Benedikt Alkin, Maximilian Beck, Korbinian Pöppel, Sepp Hochreiter, Johannes Brandstetter

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

NeuralDEM - Real-time Simulation of Industrial Particulate Flows.

Benedikt Alkin, Tobias Kronlachner, Samuele Papa, Stefan Pirker, Thomas Lichtenegger, Johannes Brandstetter

CoRR, 2024

Aurora: A Foundation Model of the Atmosphere.

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

CoRR, 2024

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

Florian Sestak, Lisa Schneckenreiter, Johannes Brandstetter, Sepp Hochreiter, Andreas Mayr, Günter Klambauer

CoRR, 2024

JAX-SPH: A Differentiable Smoothed Particle Hydrodynamics Framework.

Artur P. Toshev, Harish Ramachandran, Jonas A. Erbesdobler, Gianluca Galletti, Johannes Brandstetter, Nikolaus A. Adams

CoRR, 2024

Geometry-Informed Neural Networks.

Arturs Berzins, Andreas Radler, Sebastian Sanokowski, Sepp Hochreiter, Johannes Brandstetter

CoRR, 2024

Universal Physics Transformers.

Benedikt Alkin, Andreas Fürst, Simon Schmid, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter

CoRR, 2024

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

Benedikt Alkin, Lukas Miklautz, Sepp Hochreiter, Johannes Brandstetter

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators.

Benedikt Alkin, Andreas Fürst, Simon Schmid, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Clifford-Steerable Convolutional Neural Networks.

Maksim Zhdanov, David Ruhe, Maurice Weiler, Ana Lucic, Johannes Brandstetter, Patrick Forré

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics.

Artur P. Toshev, Jonas A. Erbesdobler, Nikolaus A. Adams, Johannes Brandstetter

Proceedings of the Forty-first International Conference on Machine Learning, 2024

GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural Networks.

Lisa Schneckenreiter, Richard Freinschlag, Florian Sestak, Johannes Brandstetter, Günter Klambauer, Andreas Mayr

Proceedings of the Second Tiny Papers Track at ICLR 2024, 2024

2023

Towards Multi-spatiotemporal-scale Generalized PDE Modeling.

Jayesh K. Gupta, Johannes Brandstetter

Trans. Mach. Learn. Res., 2023

E(3) Equivariant Graph Neural Networks for Particle-Based Fluid Mechanics.

Artur P. Toshev, Gianluca Galletti, Johannes Brandstetter, Stefan Adami, Nikolaus A. Adams

CoRR, 2023

G-Signatures: Global Graph Propagation With Randomized Signatures.

Bernhard Schäfl, Lukas Gruber, Johannes Brandstetter, Sepp Hochreiter

CoRR, 2023

Clifford Group Equivariant Neural Networks.

David Ruhe, Johannes Brandstetter, Patrick Forré

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers.

Phillip Lippe, Bas Veeling, Paris Perdikaris, Richard E. Turner, Johannes Brandstetter

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Lie Point Symmetry and Physics-Informed Networks.

Tara Akhound-Sadegh, Laurence Perreault Levasseur, Johannes Brandstetter, Max Welling, Siamak Ravanbakhsh

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Geometric Clifford Algebra Networks.

David Ruhe, Jayesh K. Gupta, Steven De Keninck, Max Welling, Johannes Brandstetter

Proceedings of the International Conference on Machine Learning, 2023

ClimaX: A foundation model for weather and climate.

Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K. Gupta, Aditya Grover

Proceedings of the International Conference on Machine Learning, 2023

Clifford Neural Layers for PDE Modeling.

Johannes Brandstetter, Rianne van den Berg, Max Welling, Jayesh K. Gupta

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Boundary Graph Neural Networks for 3D Simulations.

Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

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 Antonio Arjona-Medina, Sepp Hochreiter

Proceedings of the International Conference on Machine Learning, 2022

Lie Point Symmetry Data Augmentation for Neural PDE Solvers.

Johannes Brandstetter, Max Welling, Daniel E. Worrall

Proceedings of the International Conference on Machine Learning, 2022

Message Passing Neural PDE Solvers.

Johannes Brandstetter, Daniel E. Worrall, Max Welling

Proceedings of the Tenth International Conference on Learning Representations, 2022

Geometric and Physical Quantities improve E(3) Equivariant Message Passing.

Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik J. Bekkers, Max Welling

Proceedings of the Tenth International Conference on Learning Representations, 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

Proceedings of the Conference on Lifelong Learning Agents, 2022

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

Learning 3D Granular Flow Simulations.

Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter

CoRR, 2021

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, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter

Proceedings of the 9th International Conference on Learning Representations, 2021

Learning Lagrangian Fluid Mechanics with E(3)-Equivariant Graph Neural Networks.

Artur P. Toshev, Gianluca Galletti, Johannes Brandstetter, Stefan Adami, Nikolaus A. Adams

Proceedings of the Geometric Science of Information - 6th International Conference, 2021

2020

Cross-Domain Few-Shot Learning by Representation Fusion.

Thomas Adler, Johannes Brandstetter, Michael Widrich, Andreas Mayr, David P. Kreil, Michael Kopp, Günter Klambauer, Sepp Hochreiter

CoRR, 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, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter

CoRR, 2020

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

XAI and Strategy Extraction via Reward Redistribution.

Marius-Constantin Dinu, Markus Hofmarcher, Vihang Prakash Patil, Matthias Dorfer, Patrick M. Blies, Johannes Brandstetter, Jose A. Arjona-Medina, Sepp Hochreiter

Proceedings of the xxAI - Beyond Explainable AI, 2020

2019

Using LSTMs for climate change assessment studies on droughts and floods.

Frederik Kratzert, Daniel Klotz, Johannes Brandstetter, Pieter-Jan Hoedt, Grey Nearing, Sepp Hochreiter

CoRR, 2019

Quantum Optical Experiments Modeled by Long Short-Term Memory.

Thomas Adler, Manuel Erhard, Mario Krenn, Johannes Brandstetter, Johannes Kofler, Sepp Hochreiter

CoRR, 2019

RUDDER: Return Decomposition for Delayed Rewards.

Jose A. Arjona-Medina, Michael Gillhofer, Michael Widrich, Thomas Unterthiner, Johannes Brandstetter, Sepp Hochreiter

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019