4.5k citations · 5.2k across the 12 of their papers we have counts for
25 papers
Traffic4cast at NeurIPS 2021 -- Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes
Christian Eichenberger, Moritz Neun, Henry Martin +34
The IARAI Traffic4cast competitions at NeurIPS 2019 and 2020 showed that neural networks can successfully predict future traffic conditions 1 hour into the future on simply aggrega…
Learning 3D Granular Flow Simulations
Andreas Mayr, Sebastian Lehner, Arno Mayrhofer +3
Recently, the application of machine learning models has gained momentum in natural sciences and engineering, which is a natural fit due to the abundance of data in these fields. H…
Modern Hopfield Networks for Few- and Zero-Shot Reaction Template Prediction
Philipp Seidl, Philipp Renz, Natalia Dyubankova +6
Finding synthesis routes for molecules of interest is an essential step in the discovery of new drugs and materials. To find such routes, computer-assisted synthesis planning (CASP…
Trusted Artificial Intelligence: Towards Certification of Machine Learning Applications
Philip Matthias Winter, Sebastian Eder, Johannes Weissenböck +5
Artificial Intelligence is one of the fastest growing technologies of the 21st century and accompanies us in our daily lives when interacting with technical applications. However,…
MC-LSTM: Mass-Conserving LSTM
Pieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz +5
The success of Convolutional Neural Networks (CNNs) in computer vision is mainly driven by their strong inductive bias, which is strong enough to allow CNNs to solve vision-related…
Uncertainty Estimation with Deep Learning for Rainfall-Runoff Modelling
Daniel Klotz, Frederik Kratzert, Martin Gauch +4
Deep Learning is becoming an increasingly important way to produce accurate hydrological predictions across a wide range of spatial and temporal scales. Uncertainty estimations are…