no code implementations • 11 Sep 2023 • Matthias Karlbauer, Nathaniel Cresswell-Clay, Raul A. Moreno, Dale R. Durran, Thorsten Kurth, Martin V. Butz
We present a parsimonious deep learning weather prediction model on the Hierarchical Equal Area isoLatitude Pixelization (HEALPix) to forecast seven atmospheric variables for arbitrarily long lead times on a global approximately 110 km mesh at 3h time resolution.
no code implementations • 6 Apr 2023 • Jannik Thuemmel, Matthias Karlbauer, Sebastian Otte, Christiane Zarfl, Georg Martius, Nicole Ludwig, Thomas Scholten, Ulrich Friedrich, Volker Wulfmeyer, Bedartha Goswami, Martin V. Butz
We show how the design choices made in each of the five design elements relate to structural assumptions.
1 code implementation • 26 May 2022 • Manuel Traub, Sebastian Otte, Tobias Menge, Matthias Karlbauer, Jannik Thümmel, Martin V. Butz
Moreover, it can anticipate object motion and interactions, which are crucial abilities for conceptual planning and reasoning.
Ranked #1 on Video Object Tracking on CATER
1 code implementation • 23 Nov 2021 • Matthias Karlbauer, Timothy Praditia, Sebastian Otte, Sergey Oladyshkin, Wolfgang Nowak, Martin V. Butz
We introduce a compositional physics-aware FInite volume Neural Network (FINN) for learning spatiotemporal advection-diffusion processes.
1 code implementation • 13 Apr 2021 • Timothy Praditia, Matthias Karlbauer, Sebastian Otte, Sergey Oladyshkin, Martin V. Butz, Wolfgang Nowak
To tackle this issue, we introduce a new approach called the Finite Volume Neural Network (FINN).
no code implementations • 2 Oct 2020 • Sebastian Otte, Matthias Karlbauer, Martin V. Butz
We introduce Active Tuning, a novel paradigm for optimizing the internal dynamics of recurrent neural networks (RNNs) on the fly.
no code implementations • 21 Sep 2020 • Matthias Karlbauer, Tobias Menge, Sebastian Otte, Hendrik P. A. Lensch, Thomas Scholten, Volker Wulfmeyer, Martin V. Butz
Knowledge about the hidden factors that determine particular system dynamics is crucial for both explaining them and pursuing goal-directed interventions.
no code implementations • 19 Sep 2020 • Matthias Karlbauer, Sebastian Otte, Hendrik P. A. Lensch, Thomas Scholten, Volker Wulfmeyer, Martin V. Butz
The novel DISTributed Artificial neural Network Architecture (DISTANA) is a generative, recurrent graph convolution neural network.
1 code implementation • 23 Dec 2019 • Matthias Karlbauer, Sebastian Otte, Hendrik P. A. Lensch, Thomas Scholten, Volker Wulfmeyer, Martin V. Butz
We introduce a distributed spatio-temporal artificial neural network architecture (DISTANA).