Variational Information Bottleneck for Unsupervised Clustering: Deep
Gaussian Mixture Embedding

v1v2v3 (latest)

Variational Information Bottleneck for Unsupervised Clustering: Deep Gaussian Mixture Embedding

Entropy (Entropy), 2019

28 May 2019

George Arvanitakis

Milad Sefidgaran

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Papers citing "Variational Information Bottleneck for Unsupervised Clustering: Deep Gaussian Mixture Embedding"

8 / 8 papers shown

Title
The Wyner Variational Autoencoder for Unsupervised Multi-Layer Wireless FingerprintingGlobal Communications Conference (GLOBECOM), 2023 Tengfei Huang T. Dahanayaka Kanchana Thilakarathna Philip H. W. Leong H. El Gamal 162 3 0 28 Mar 2023
Clustering based on Mixtures of Sparse Gaussian Processes Zahra Moslehi Abdolreza Mirzaei M. Safayani 58 0 0 23 Mar 2023
A generative recommender system with GMM prior for cancer drug generation and sensitivity prediction Krzysztof Koras Marcin Mo.zejko Paula Szymczak E. Staub Ewa Szczurek 138 0 0 07 Jun 2022
Deep Graph Clustering via Mutual Information Maximization and Mixture ModelKnowledge and Information Systems (KAIS), 2022 Maedeh Ahmadi M. Safayani Abdolreza Mirzaei 209 8 0 10 May 2022
Multiple Importance Sampling ELBO and Deep Ensembles of Variational ApproximationsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 Oskar Kviman Harald Melin Hazal Koptagel Victor Elvira J. Lagergren DRL 182 18 0 22 Feb 2022
Joint Optimization of an Autoencoder for Clustering and Embedding Ahcène Boubekki Michael C. Kampffmeyer Robert Jenssen Ulf Brefeld DRL 320 22 0 07 Dec 2020
Unsupervised Embedding of Hierarchical Structure in Euclidean Space Jinyu Zhao Yi Hao Cyrus Rashtchian DRL 119 3 0 30 Oct 2020
SeGMA: Semi-Supervised Gaussian Mixture Auto-EncoderIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2019 Marek Śmieja Maciej Wołczyk Jacek Tabor Bernhard C. Geiger 158 24 0 21 Jun 2019