Ralf Mikut

Head of Research Area

Karlsruhe Institute of Technology

Germany

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About

Ralf Mikut is the Head of Research Area at the Karlsruhe Institute of Technology, Germany. His research interests include probabilistic scheduling for grid operations, AI applications in coverage path planning, and the variability in mouse stem cell-derived embryo models. Recent publications reflect his work in automating quantile estimation, process monitoring in laser welding, and generating synthetic energy time series.

Articles (19)

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Collaborators (10)

Fernando Díaz de María

Universidad Carlos III de Madrid

SPAIN

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Benjamin Schäfer

Assistant Professor

Karlsruhe Institute of Technology

GERMANY

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Julian Schröter

Heidelberg University

GERMANY

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Magdalena Zernicka-Goetz

Professor and PI

California Institute of Technology

UNITED STATES

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Kristof Van Laerhoven

Professor

University of Siegen

GERMANY

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Peter Burggräf

Full Professor

Universität Siegen Naturwissenschaftlich-Technische Fakultät

GERMANY

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IVAN GONZALEZ

Universidad Carlos III de Madrid

SPAIN

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Heidi S. Nygård

Norwegian University of Life Sciences

NORWAY

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Lennart Hilbert

Junior Prof. Systems Biology/Bioinformatics

Karlsruhe Institute of Technology

GERMANY

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Pere Colet

Instituto de Física Interdisciplinar y Sistemas Complejos

SPAIN

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Ralf Mikut

Research Interests

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Articles (19)

AI-based approach to dissect the variability of mouse stem cell-derived embryo models

Probabilistic day-ahead battery scheduling based on mixed random variables for enhanced grid operation

Rapid AI-based generation of coverage paths for dispensing applications

AutoPQ: Automating quantile estimation from point forecasts in the context of sustainability

TIMtrace: Coverage Path Planning for Thermal Interface Materials

Event-based vision in laser welding: An approach for process monitoring

Generating peak‐aware pseudo‐measurements for low‐voltage feeders using metadata of distribution system operators

ASAP: Automated Style-Aware Similarity Measurement for Selection of Annotated Pre-Training Datasets in 2D Biomedical Imaging

Generating synthetic energy time series: A review

A self-supervised embedding of cell migration features for behavior discovery over cell populations

The impact of heat pumps on day-ahead energy community load forecasting

Using conditional Invertible Neural Networks to perform mid‐term peak load forecasting

A large and diverse brain organoid dataset of 1,400 cross-laboratory images of 64 trackable brain organoids

Generating probabilistic forecasts from arbitrary point forecasts using a conditional invertible neural network

Rapid Flow Behavior Modeling of Thermal Interface Materials Using Deep Neural Networks

Context-aware composition of agent policies by Markov decision process entity embeddings and agent ensembles

Predicting the power grid frequency of European islands

Noise facilitates entrainment of a population of uncoupled limit cycle oscillators

Controlling non-stationarity and periodicities in time series generation using conditional invertible neural networks

Collaborators (10)

Fernando Díaz de María

Benjamin Schäfer

Julian Schröter

Magdalena Zernicka-Goetz

Kristof Van Laerhoven

Peter Burggräf

IVAN GONZALEZ

Heidi S. Nygård

Lennart Hilbert

Pere Colet

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