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08/28/2023
Context-Aware Composition of Agent Policies by Markov Decision Process Entity Embeddings and Agent Ensembles
Computational agents support humans in many areas of life and are theref...
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06/19/2023
Transformer Training Strategies for Forecasting Multiple Load Time Series
Recent work uses Transformers for load forecasting, which are the state ...
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02/06/2023
ProbPNN: Enhancing Deep Probabilistic Forecasting with Statistical Information
Probabilistic forecasts are essential for various downstream application...
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02/03/2023
Creating Probabilistic Forecasts from Arbitrary Deterministic Forecasts using Conditional Invertible Neural Networks
In various applications, probabilistic forecasts are required to quantif...
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12/13/2022
AutoPV: Automated photovoltaic forecasts with limited information using an ensemble of pre-trained models
Accurate PhotoVoltaic (PV) power generation forecasting is vital for the...
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11/26/2022
EasyMLServe: Easy Deployment of REST Machine Learning Services
Various research domains use machine learning approaches because they ca...
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09/27/2022
Predicting the power grid frequency of European islands
Modelling, forecasting and overall understanding of the dynamics of the ...
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08/08/2022
Rapid Flow Behavior Modeling of Thermal Interface Materials Using Deep Neural Networks
Thermal Interface Materials (TIMs) are widely used in electronic packagi...
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04/22/2022
EmbedTrack – Simultaneous Cell Segmentation and Tracking Through Learning Offsets and Clustering Bandwidths
A systematic analysis of the cell behavior requires automated approaches...
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04/16/2022
Exploiting Multiple EEG Data Domains with Adversarial Learning
Electroencephalography (EEG) is shown to be a valuable data source for e...
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02/25/2022
ciscNet – A Single-Branch Cell Instance Segmentation and Classification Network
Automated cell nucleus segmentation and classification are required to a...
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02/03/2022
Review of automated time series forecasting pipelines
Time series forecasting is fundamental for various use cases in differen...
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01/27/2022
Domain-Invariant Representation Learning from EEG with Private Encoders
Deep learning based electroencephalography (EEG) signal processing metho...
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11/27/2021
Label Assistant: A Workflow for Assisted Data Annotation in Image Segmentation Tasks
Recent research in the field of computer vision strongly focuses on deep...
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11/17/2021
Smart Data Representations: Impact on the Accuracy of Deep Neural Networks
Deep Neural Networks are able to solve many complex tasks with less engi...
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10/26/2021
Concepts for Automated Machine Learning in Smart Grid Applications
Undoubtedly, the increase of available data and competitive machine lear...
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06/18/2021
pyWATTS: Python Workflow Automation Tool for Time Series
Time series data are fundamental for a variety of applications, ranging ...
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01/20/2021
Probabilistic Solar Power Forecasting: Long Short-Term Memory Network vs Simpler Approaches
The high penetration of volatile renewable energy sources such as solar ...
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01/05/2021
Data-Driven Copy-Paste Imputation for Energy Time Series
A cornerstone of the worldwide transition to smart grids are smart meter...
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09/29/2020
Evaluating Ensemble Post-Processing for Wind Power Forecasts
Capturing the uncertainty in probabilistic wind power forecasts is chall...
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09/25/2020
CAD2Real: Deep learning with domain randomization of CAD data for 3D pose estimation of electronic control unit housings
Electronic control units (ECUs) are essential for many automobile compon...
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05/29/2020
Design of Transformation Initiatives Implementing Organisational Agility – An Empirical Study
This study uses 125 responses from companies of all sizes headquartered ...
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04/03/2020
Cell Segmentation and Tracking using Distance Transform Predictions and Movement Estimation with Graph-Based Matching
In this paper, we present the approach used for our IEEE ISBI 2020 Cell ...
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01/30/2020
Semi-Automatic Generation of Tight Binary Masks and Non-Convex Isosurfaces for Quantitative Analysis of 3D Biological Samples
Current in vivo microscopy allows us detailed spatiotemporal imaging (3D...
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10/14/2019
Data-driven charging strategies for grid-beneficial, customer-oriented and battery-preserving electric mobility
Electric Vehicle (EV) penetration and renewable energies enables synergi...
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03/18/2019
Probabilistic Energy Forecasting using Quantile Regressions based on a new Nearest Neighbors Quantile Filter
Parametric quantile regressions are a useful tool for creating probabili...
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06/19/2018
Transfer Learning with Human Corneal Tissues: An Analysis of Optimal Cut-Off Layer
Transfer learning is a powerful tool to adapt trained neural networks to...
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05/15/2018
Digital Transformation in Airport Ground Operations
How has digital transformation changed airport ground operations? Althou...
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10/18/2017
Cell Segmentation in 3D Confocal Images using Supervoxel Merge-Forests with CNN-based Hypothesis Selection
Automated segmentation approaches are crucial to quantitatively analyze ...
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01/16/2017
Datenqualität in Regressionsproblemen
Regression models are increasingly built using datasets which do not fol...
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08/03/2016
Fuzzy-based Propagation of Prior Knowledge to Improve Large-Scale Image Analysis Pipelines
Many automatically analyzable scientific questions are well-posed and of...
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04/17/2016
Generating Semi-Synthetic Validation Benchmarks for Embryomics
Systematic validation is an essential part of algorithm development. The...
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02/09/2016