A Distributed Neural Network Architecture for Robust Non-Linear Spatio-Temporal Prediction. - Matthias Karlbauer; Sebastian Otte; Hendrik P. A. Lensch; Thomas Scholten; Volker Wulfmeyer; Martin V. Butz (ESANN, 2020)

Inferring, Predicting, and Denoising Causal Wave Dynamics. - Matthias Karlbauer; Sebastian Otte; Hendrik P. A. Lensch; Thomas Scholten; Volker Wulfmeyer; Martin V. Butz (ICANN (1), 2020)

Hidden Latent State Inference in a Spatio-Temporal Generative Model. - Matthias Karlbauer; Tobias Menge; Sebastian Otte; Hendrik P. A. Lensch; Thomas Scholten; Volker Wulfmeyer; Martin V. Butz (CoRR, 2020)

Active Tuning. - Sebastian Otte; Matthias Karlbauer; Martin V. Butz (CoRR, 2020)

Signal Denoising with Recurrent Spiking Neural Networks and Active Tuning. - Melvin Ciurletti; Manuel Traub; Matthias Karlbauer; Martin V. Butz; Sebastian Otte (ICANN (5), 2021)

Latent State Inference in a Spatiotemporal Generative Model. - Matthias Karlbauer; Tobias Menge; Sebastian Otte; Hendrik P. A. Lensch; Thomas Scholten; Volker Wulfmeyer; Martin V. Butz (ICANN (4), 2021)

Finite Volume Neural Network: Modeling Subsurface Contaminant Transport. - Timothy Praditia; Matthias Karlbauer; Sebastian Otte; Sergey Oladyshkin; Martin V. Butz; Wolfgang Nowak (CoRR, 2021)

Infering Boundary Conditions in Finite Volume Neural Networks. - Cosku Can Horuz; Matthias Karlbauer; Timothy Praditia; Martin V. Butz; Sergey Oladyshkin; Wolfgang Nowak; Sebastian Otte (ICANN (1), 2022)

Composing Partial Differential Equations with Physics-Aware Neural Networks. - Matthias Karlbauer; Timothy Praditia; Sebastian Otte; Sergey Oladyshkin; Wolfgang Nowak; Martin V. Butz (ICML, 2022)

Learning What and Where - Unsupervised Disentangling Location and Identity Tracking. - Manuel Traub; Sebastian Otte; Tobias Menge; Matthias Karlbauer; Jannik Thümmel; Martin V. Butz (CoRR, 2022)

Finite Volume Neural Network. - Timothy Praditia; Matthias Karlbauer; Sebastian Otte; Sergey Oladyshkin; Martin V. Butz; Wolfang Nowak (Zenodo, 2022)

Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network. - Timothy Praditia; Matthias Karlbauer; Sebastian Otte; Sergey Oladyshkin; Martin V. Butz; Wolfgang Nowak (DaRUS, 2022)

Learning What and Where: Disentangling Location and Identity Tracking Without Supervision. - Manuel Traub; Sebastian Otte; Tobias Menge; Matthias Karlbauer; Jannik Thümmel; Martin V. Butz (ICLR, 2023)

Inductive biases in deep learning models for weather prediction. - Jannik Thümmel; Matthias Karlbauer; Sebastian Otte; Christiane Zarfl; Georg Martius; Nicole Ludwig 002; Thomas Scholten; Ulrich Friedrich; Volker Wulfmeyer; Bedartha Goswami; Martin V. Butz (CoRR, 2023)

Advancing Parsimonious Deep Learning Weather Prediction using the HEALPix Mesh. - Matthias Karlbauer; Nathaniel Cresswell-Clay; Raul A. Moreno; Dale R. Durran; Thorsten Kurth; Martin V. Butz (CoRR, 2023)

Extending the Omniglot Challenge: Imitating Handwriting Styles on a New Sequential Data Set. - Sarah Fabi; Sebastian Otte; Fedor Scholz; Julius Wührer; Matthias Karlbauer; Martin V. Butz (IEEE Trans. Cogn. Dev. Syst., 2023)

Physical Domain Reconstruction with Finite Volume Neural Networks. - Cosku Can Horuz; Matthias Karlbauer; Timothy Praditia; Martin V. Butz; Sergey Oladyshkin; Wolfgang Nowak; Sebastian Otte (Appl. Artif. Intell., 2023)

Comparing and Contrasting Deep Learning Weather Prediction Backbones on Navier-Stokes and Atmospheric Dynamics. - Matthias Karlbauer; Danielle C. Maddix; Abdul Fatir Ansari; Boran Han; Gaurav Gupta; Yuyang Wang 001; Andrew Stuart; Michael W. Mahoney (CoRR, 2024)

Inferring Underwater Topography with FINN. - Cosku Can Horuz; Matthias Karlbauer; Timothy Praditia; Sergey Oladyshkin; Wolfgang Nowak; Sebastian Otte (CoRR, 2024)

Minimal Convolutional RNNs Accelerate Spatiotemporal Learning. - Cosku Can Horuz; Sebastian Otte; Martin V. Butz; Matthias Karlbauer (CoRR, 2025)