4.5k citations · 8.5k across the 90 of their papers we have counts for
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Detecting cutaneous basal cell carcinomas in ultra-high resolution and weakly labelled histopathological images
Susanne Kimeswenger, Elisabeth Rumetshofer, Markus Hofmarcher +5
Diagnosing basal cell carcinomas (BCC), one of the most common cutaneous malignancies in humans, is a task regularly performed by pathologists and dermato-pathologists. Improving h…
Using LSTMs for climate change assessment studies on droughts and floods
Frederik Kratzert, Daniel Klotz, Johannes Brandstetter +3
Climate change affects occurrences of floods and droughts worldwide. However, predicting climate impacts over individual watersheds is difficult, primarily because accurate hydrolo…
Quantum Optical Experiments Modeled by Long Short-Term Memory
Thomas Adler, Manuel Erhard, Mario Krenn +3
We demonstrate how machine learning is able to model experiments in quantum physics. Quantum entanglement is a cornerstone for upcoming quantum technologies such as quantum computa…
Patch Refinement -- Localized 3D Object Detection
Johannes Lehner, Andreas Mitterecker, Thomas Adler +3
We introduce Patch Refinement a two-stage model for accurate 3D object detection and localization from point cloud data. Patch Refinement is composed of two independently trained V…
Explaining and Interpreting LSTMs
Leila Arras, Jose A. Arjona-Medina, Michael Widrich +5
While neural networks have acted as a strong unifying force in the design of modern AI systems, the neural network architectures themselves remain highly heterogeneous due to the v…
Towards Learning Universal, Regional, and Local Hydrological Behaviors via Machine-Learning Applied to Large-Sample Datasets
Frederik Kratzert, Daniel Klotz, Guy Shalev +3
Regional rainfall-runoff modeling is an old but still mostly out-standing problem in Hydrological Sciences. The problem currently is that traditional hydrological models degrade si…
Interpretable Deep Learning in Drug Discovery
Kristina Preuer, Günter Klambauer, Friedrich Rippmann +2
Without any means of interpretation, neural networks that predict molecular properties and bioactivities are merely black boxes. We will unravel these black boxes and will demonstr…
NeuralHydrology -- Interpreting LSTMs in Hydrology
Frederik Kratzert, Mathew Herrnegger, Daniel Klotz +2
Despite the huge success of Long Short-Term Memory networks, their applications in environmental sciences are scarce. We argue that one reason is the difficulty to interpret the in…