105 citations · 441 across the 38 of their papers we have counts for
6 papers · 1 filter
MLOps for Scarce Image Data: A Use Case in Microscopic Image Analysis
Angelo Yamachui Sitcheu, Nils Friederich, Simon Baeuerle +3
Nowadays, Machine Learning (ML) is experiencing tremendous popularity that has never been seen before. The operationalization of ML models is governed by a set of concepts and meth…
Context-Aware Composition of Agent Policies by Markov Decision Process Entity Embeddings and Agent Ensembles
Nicole Merkle, Ralf Mikut
Computational agents support humans in many areas of life and are therefore found in heterogeneous contexts. This means they operate in rapidly changing environments and can be con…
Transformer Training Strategies for Forecasting Multiple Load Time Series
Matthias Hertel, Maximilian Beichter, Benedikt Heidrich +4
In the smart grid of the future, accurate load forecasts on the level of individual clients can help to balance supply and demand locally and to prevent grid outages. While the num…
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting
Simon Graham, Quoc Dang Vu, Mostafa Jahanifar +86
Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovatio…
ProbPNN: Enhancing Deep Probabilistic Forecasting with Statistical Information
Benedikt Heidrich, Kaleb Phipps, Oliver Neumann +3
Probabilistic forecasts are essential for various downstream applications such as business development, traffic planning, and electrical grid balancing. Many of these probabilistic…
Creating Probabilistic Forecasts from Arbitrary Deterministic Forecasts using Conditional Invertible Neural Networks
Kaleb Phipps, Benedikt Heidrich, Marian Turowski +3
In various applications, probabilistic forecasts are required to quantify the inherent uncertainty associated with the forecast. However, numerous modern forecasting methods are st…