4.5k citations · 5.3k across the 19 of their papers we have counts for
4 papers · 1 filter
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…
Cross-Domain Few-Shot Learning by Representation Fusion
Thomas Adler, Johannes Brandstetter, Michael Widrich +5
In order to quickly adapt to new data, few-shot learning aims at learning from few examples, often by using already acquired knowledge. The new data often differs from the previous…
Modern Hopfield Networks and Attention for Immune Repertoire Classification
Michael Widrich, Bernhard Schäfl, Hubert Ramsauer +8
A central mechanism in machine learning is to identify, store, and recognize patterns. How to learn, access, and retrieve such patterns is crucial in Hopfield networks and the more…
Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks
Markus Hofmarcher, Andreas Mayr, Elisabeth Rumetshofer +8
Due to the current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, there is an urgent need for novel therapies and drugs. We conducted a large-scale virtual…