Towards learning universal, regional, and local hydrologicalbehaviors via machine learning applied tolarge-sample datasets

Toward Improved Predictions in Ungauged Basins: Exploiting the Power of Machine Learning

Machine Learning in Drug Discovery

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
 

On the Convergence of Episodic Reinforcement Learning Algorithms at the Example of RUDDER

A Two Time-Scale Update Rule Ensuring Convergence of Episodic Reinforcement Learning Algorithms at the Example of RUDDER

Industry-scale Application and Evaluation of Deep Learning for Drug Target Prediction

A GAN based solver idea for derivative-free optimization problems

A GAN based solver of black-box inverse problems

Uncertainty Estimation Methods to Support Decision-Making in Early Phases of Drug Discovery

Patch Refinement: Localized 3D Object Detection

LSTM-Designed Quantum Experiments

Using LSTMs for climate change assessment studies on droughts and floods

RUDDER: Return Decomposition for Delayed Rewards

Human-level Protein Localization with Convolutional Neural Networks _ICLR

Detecting cutaneous basal cell carcinomas in ultra-high resolution and weakly labelled histopathological images

Towards the quantification of uncertainty for deep learning based rainfall-runoff models _EGU

Using large data sets towards generating a catchment aware hydrological model for global applications _EGU

Explaining and Interpreting LSTMs _{Explainable AI: Interpreting, Explaining and Visualizing Deep Learning}

Visual Scene Understanding for Autonomous Driving Using Semantic Segmentation _{Explainable AI: Interpreting, Explaining and Visualizing Deep Learning}

Interpretable Deep Learning in Drug Discovery _{Explainable AI: Interpreting, Explaining and Visualizing Deep Learning}

NeuralHydrology – Interpreting LSTMs in Hydrology _{Explainable AI: Interpreting, Explaining and Visualizing Deep Learning}