Density-Based Clustering Based on Hierarchical Density Estimates

UCI Machine Learning Repository

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ROBP a robust border-peeling clustering using Cauchy kernel

Du, M., Wang, R., Ji, R., Wang, X., & Dong, Y. (2021) · Information Sciences · doi:10.1016/j.ins.2021.04.089 · Cited by 24

Constraint-Based Hierarchical Cluster Selection in Automotive Radar Data

Malzer, C., & Baum, M. (2021) · Sensors · doi:10.3390/s21103410 · Cited by 24

Integration of theory, simulation, artificial intelligence and virtual reality: a four-pillar approach for reconciling accuracy and interpretability in computational spectroscopy

Barone, V., Puzzarini, C., & Mancini, G. (2021) · Physical Chemistry Chemical Physics · doi:10.1039/d1cp02507d · Cited by 24

Probiotic Mixture Containing Lactobacillus helveticus, Bifidobacterium longum and Lactiplantibacillus plantarum Affects Brain Responses Toward an Emotional Task in Healthy Subjects: A Randomized Clinical Trial

Rode, J., Carlman, H. M. T. E., König, J., Repsilber, D., Hutchinson, A. N., Thunberg, P., Andersson, P., Persson, J., Kiselev, A., Stern, L. L., et al. (2022) · Frontiers in Nutrition · doi:10.3389/fnut.2022.827182 · Cited by 25

The formation of clusters and OB associations in different density spiral arm environments

Dobbs, C. L., Bending, T. J. R., Pettitt, A. R., Buckner, A. S. M., & Bate, M. R. (2022) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stac2474 · Cited by 24

Does Fake News in Different Languages Tell the Same Story? An Analysis of Multi-level Thematic and Emotional Characteristics of News about COVID-19

Zhou, L., Tao, J., & Zhang, D. (2022) · Information Systems Frontiers · doi:10.1007/s10796-022-10329-7 · Cited by 28

Endogenous tagging of Unc-13 reveals nanoscale reorganization at active zones during presynaptic homeostatic potentiation

Dannhäuser, S., Mrestani, A., Gundelach, F., Pauli, M., Komma, F., Kollmannsberger, P., Sauer, M., Heckmann, M., & Paul, M. M. (2022) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2022.1074304 · Cited by 22

ExBEHRT: Extended Transformer for Electronic Health Records

Rupp, M., Peter, O., & Pattipaka, T. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-39539-0_7 · Cited by 27

Microscopic defect dynamics during a brittle-to-ductile transition

O’Ghaffari, H., Peč, M., Mittal, T., Mok, U., Chang, H., & Evans, B. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2305667120 · Cited by 24

An Alternating Optimization Approach Based on Hierarchical Adaptations of DBSCAN

Dockhorn, A., Braune, C., & Kruse, R. (2015) · IEEE Symposium Series on Computational Intelligence (SSCI) · doi:10.1109/ssci.2015.113 · Cited by 24

optimalFlow: optimal transport approach to flow cytometry gating and population matching

del Barrio, E., Inouzhe, H., Loubes, J., Matrán, C., & Mayo-Íscar, A. (2020) · BMC Bioinformatics · doi:10.1186/s12859-020-03795-w · Cited by 23

Stability of density-based clustering

RinaldoAlessandro, SinghAarti, NugentRebecca, & WassermanLarry (2012) · Journal of Machine Learning Research · doi:10.5555/2503308.2503309 · Cited by 1

Stable and consistent density-based clustering.Preprint

Rolle, A., & Scoccola, L. (2020) · arXiv (Cornell University) · Cited by 12

Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection

Campello, R. J. G. B., Moulavi, D., Zimek, A., & Sander, J. (2015) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/2733381 · Cited by 915

Density‐based clustering

Campello, R. J. G. B., Kröger, P., Sander, J., & Zimek, A. (2019) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.1343 · Cited by 142

A New Accurate Clustering Approach for Detecting Different Densities in High Dimensional Data

Malki, N. E., Cugny, R., Teste, O., & Ravat, F. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-86534-4_16 · Cited by 13