Christian Beecks
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View article: Structuring Data Science Automation: A Competency-Aware Taxonomy Approach
Structuring Data Science Automation: A Competency-Aware Taxonomy Approach Open
View article: KINLI: Time Series Forecasting for Monitoring Poultry Health in Complex Pen Environments
KINLI: Time Series Forecasting for Monitoring Poultry Health in Complex Pen Environments Open
We analyze how to perform accurate time series forecasting for monitoring poultry health in a complex pen environment. To this end, we make use of a novel dataset consisting of a collection of real-world sensor data in the housing of turke…
View article: Automated Exploratory Clustering to Democratize Clustering Analysis
Automated Exploratory Clustering to Democratize Clustering Analysis Open
AutoML is enabling many practitioners to use sophisticated Machine Learning pipelines even without being experienced in building application-specific solutions. Adapting AutoML to the field of unsupervised learning, particularly to the tas…
View article: AI-driven transformation in food manufacturing: a pathway to sustainable efficiency and quality assurance
AI-driven transformation in food manufacturing: a pathway to sustainable efficiency and quality assurance Open
This study aims to explore the transformative role of Artificial Intelligence (AI) in food manufacturing by optimizing production, reducing waste, and enhancing sustainability. This review follows a literature review approach, synthesizing…
View article: Wissenschaftlichkeit vs. Praxisbezug
Wissenschaftlichkeit vs. Praxisbezug Open
View article: Wissenschaftlichkeit vs. Praxisbezug
Wissenschaftlichkeit vs. Praxisbezug Open
View article: Arbitrary Shaped Clustering Validation on the Test Bench
Arbitrary Shaped Clustering Validation on the Test Bench Open
View article: Towards a Standardized Data Science Competence Framework: A Literature Review Approach
Towards a Standardized Data Science Competence Framework: A Literature Review Approach Open
View article: <b>Resolving spatiotemporal electrical signaling within the islet via CMOS microelectrode arrays</b>
<b>Resolving spatiotemporal electrical signaling within the islet via CMOS microelectrode arrays</b> Open
Glucose-stimulated beta-cells exhibit synchronized calcium dynamics across the islet that recruit beta-cells to enhance insulin secretion. Compared to calcium dynamics, the formation and cell-to-cell propagation of electrical signals withi…
View article: <b>Resolving spatiotemporal electrical signaling within the islet via CMOS microelectrode arrays</b>
<b>Resolving spatiotemporal electrical signaling within the islet via CMOS microelectrode arrays</b> Open
Glucose-stimulated beta-cells exhibit synchronized calcium dynamics across the islet that recruit beta-cells to enhance insulin secretion. Compared to calcium dynamics, the formation and cell-to-cell propagation of electrical signals withi…
View article: On the Laplace Approximation as Model Selection Criterion for Gaussian Processes
On the Laplace Approximation as Model Selection Criterion for Gaussian Processes Open
Model selection aims to find the best model in terms of accuracy, interpretability or simplicity, preferably all at once. In this work, we focus on evaluating model performance of Gaussian process models, i.e. finding a metric that provide…
View article: AI Lifecycle Zero-Touch Orchestration within the Edge-to-Cloud Continuum for Industry 5.0
AI Lifecycle Zero-Touch Orchestration within the Edge-to-Cloud Continuum for Industry 5.0 Open
The advancements in human-centered artificial intelligence (HCAI) systems for Industry 5.0 is a new phase of industrialization that places the worker at the center of the production process and uses new technologies to increase prosperity …
View article: Resolving spatiotemporal electrical signaling within the islet via CMOS microelectrode arrays
Resolving spatiotemporal electrical signaling within the islet via CMOS microelectrode arrays Open
Glucose-stimulated beta-cells synchronize calcium waves across the islet to recruit more beta-cells for insulin secretion. Compared to calcium dynamics, the formation and cell-to-cell propagation of electrical signals within the islet are …
View article: Anomaly Detection in Manufacturing
Anomaly Detection in Manufacturing Open
This chapter provides an introduction to common methods of anomaly detection, which is an important aspect of quality control in manufacturing. We give an overview of widely used statistical methods for detecting anomalies based on k-means…
View article: Designing a Marketplace to Exchange AI Models for Industry 5.0
Designing a Marketplace to Exchange AI Models for Industry 5.0 Open
Nowadays, the market for AI services is continuously growing and it is expected to exceed 5 trillion euros in the next 5 years. However, the sharing of knowledge is primarily achieved by the sharing of published AI-related papers. The shar…
View article: Industry 4.0: Mining physical defects in production of surface-mount devices
Industry 4.0: Mining physical defects in production of surface-mount devices Open
With the advent of Industry 4.0, production processes have been endowed with intelligent cyber-physical systems generating massive amounts of streaming sensor data. Internet of Things technologies have enabled capturing, managing, and proc…
View article: Interpreting Black-box Machine Learning Models for High Dimensional Datasets
Interpreting Black-box Machine Learning Models for High Dimensional Datasets Open
Deep neural networks (DNNs) have been shown to outperform traditional machine learning algorithms in a broad variety of application domains due to their effectiveness in modeling complex problems and handling high-dimensional datasets. Man…
View article: Automated Model Inference for Gaussian Processes: An Overview of State-of-the-Art Methods and Algorithms
Automated Model Inference for Gaussian Processes: An Overview of State-of-the-Art Methods and Algorithms Open
Gaussian process models (GPMs) are widely regarded as a prominent tool for learning statistical data models that enable interpolation, regression, and classification. These models are typically instantiated by a Gaussian Process with a zer…
View article: Dynamically Self-adjusting Gaussian Processes for Data Stream Modelling
Dynamically Self-adjusting Gaussian Processes for Data Stream Modelling Open
One of the major challenges in time series analysis are changing data distributions, especially when processing data streams. To ensure an up-to-date model delivering useful predictions at all times, model reconfigurations are required to …
View article: knowlEdge Project –Concept, Methodology and Innovations for Artificial Intelligence in Industry 4.0
knowlEdge Project –Concept, Methodology and Innovations for Artificial Intelligence in Industry 4.0 Open
AI is one of the biggest megatrends towards the 4th industrial revolution. Although these technologies promise business sustainability as well as product and process quality, it seems that the ever-changing market demands, the complexity o…
View article: Complexity-Adaptive Gaussian Process Model Inference for Large-Scale Data
Complexity-Adaptive Gaussian Process Model Inference for Large-Scale Data Open
View article: Stochastic Time Series Representation for Interval Pattern Mining via Gaussian Processes
Stochastic Time Series Representation for Interval Pattern Mining via Gaussian Processes Open
View article: A Structure-Based Platform for Predicting Chemical Reactivity
A Structure-Based Platform for Predicting Chemical Reactivity Open
View article: Large-scale Retrieval of Bayesian Machine Learning Models for Time Series Data via Gaussian Processes
Large-scale Retrieval of Bayesian Machine Learning Models for Time Series Data via Gaussian Processes Open
Gaussian Process Models (GPMs) are widely regarded as a prominent tool for learning statistical data models that enable timeseries interpolation, regression, and classification. These models are frequently instantiated by a Gaussian Proces…
View article: Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0
Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0 Open
View article: A Structure-Based Platform for Predicting Chemical Reactivity
A Structure-Based Platform for Predicting Chemical Reactivity Open
Despite their enormous potential, machine learning methods have only found limited application in predicting reaction outcomes, as current models are often highly complex and, most importantly, are not transferrable to different problem se…
View article: A Structure-Based Platform for Predicting Chemical Reactivity
A Structure-Based Platform for Predicting Chemical Reactivity Open
Despite their enormous potential, machine learning methods have only found limited application in predicting reaction outcomes, as current models are often highly complex and, most importantly, are not transferrable to different problem se…
View article: V3C1 Dataset
V3C1 Dataset Open
In this work we analyze content statistics of the V3C1 dataset, which is the first partition of theVimeo Creative Commons Collection (V3C). The dataset has been designed to represent true web videos in the wild, with good visual quality an…
View article: Incremental Deep-Learning for Continuous Load Prediction in Energy Management Systems
Incremental Deep-Learning for Continuous Load Prediction in Energy Management Systems Open
In this work, we introduce load prediction as continuous input for optimization models within an optimization framework for short-term control of complex energy systems. In this context, we investigated long short-term memory (LSTM) models…
View article: Data analysis and visualization framework in the manufacturing decision support system of COMPOSITION project
Data analysis and visualization framework in the manufacturing decision support system of COMPOSITION project Open