A survey on unsupervised outlier detection in high‐dimensional numerical data
High‐dimensional data in Euclidean space pose special challenges to data mining
algorithms. These challenges are often indiscriminately subsumed under the term 'curse of …
algorithms. These challenges are often indiscriminately subsumed under the term 'curse of …
Density‐based clustering
Clustering refers to the task of identifying groups or clusters in a data set. In density‐based
clustering, a cluster is a set of data objects spread in the data space over a contiguous …
clustering, a cluster is a set of data objects spread in the data space over a contiguous …
How molecular size impacts RMSD applications in molecular dynamics simulations
K Sargsyan, C Grauffel, C Lim - Journal of chemical theory and …, 2017 - ACS Publications
The root-mean-square deviation (RMSD) is a similarity measure widely used in analysis of
macromolecular structures and dynamics. As increasingly larger macromolecular systems …
macromolecular structures and dynamics. As increasingly larger macromolecular systems …
The dark machines anomaly score challenge: benchmark data and model independent event classification for the large hadron collider
T Aarrestad, M van Beekveld, M Bona, A Boveia… - SciPost Physics, 2022 - scipost.org
We describe the outcome of a data challenge conducted as part of the Dark Machines
Initiative and the Les Houches 2019 workshop on Physics at TeV colliders. The challenged …
Initiative and the Les Houches 2019 workshop on Physics at TeV colliders. The challenged …
Big Data with Cloud Computing: an insight on the computing environment, MapReduce, and programming frameworks
The term 'Big Data'has spread rapidly in the framework of Data Mining and Business
Intelligence. This new scenario can be defined by means of those problems that cannot be …
Intelligence. This new scenario can be defined by means of those problems that cannot be …
Data-driven monitoring of multimode continuous processes: A review
Abstract The Internet of Things benefits connectivity and functionality in industrial
environments, while Cloud Computing boosts computational capability. Hence, historical …
environments, while Cloud Computing boosts computational capability. Hence, historical …
Context-aware misinformation detection: A benchmark of deep learning architectures using word embeddings
New mass media paradigms for information distribution have emerged with the digital age.
With new digital-enabled mass media, the communication process is centered around the …
With new digital-enabled mass media, the communication process is centered around the …
Causal unsupervised semantic segmentation
Unsupervised semantic segmentation aims to achieve high-quality semantic grouping
without human-labeled annotations. With the advent of self-supervised pre-training, various …
without human-labeled annotations. With the advent of self-supervised pre-training, various …
[HTML][HTML] Data-driven modeling of multimode chemical process: Validation with a real-world distillation column
Real-world industrial processes frequently operate in different modes such as start-up,
transient, and steady-state operation. Since different operating modes are governed by …
transient, and steady-state operation. Since different operating modes are governed by …
Latent discriminant deterministic uncertainty
Predictive uncertainty estimation is essential for deploying Deep Neural Networks in real-
world autonomous systems. However, most successful approaches are computationally …
world autonomous systems. However, most successful approaches are computationally …