IEEE

Time-DisCo: A Disentangled Contrastive Autoencoder Approach to Enhancing Multivariate Probabilistic Time Series Forecasting From Multisensor Data

Abstract: In the context of data-driven decision-making, constructing accurate and well-generalized probabilistic forecasting models to handle dynamic, complex, and high-dimensional multivariate time ...
IEEE

Disentangled Contrastive Multi-View Clustering via Semantic Relevance Invariance

Abstract: The real-world data is relatively complex, generally formed by the interaction of different latent factors. Disentanglement of these latent factors can effectively improve the robustness and ...
GitHub

ZAYAN: Disentangled Contrastive Transformer for Tabular Remote Sensing Data

Al Zadid Sultan Bin Habib, Tanpia Tasnim, Md. Ekramul Islam, and Muntasir Tabasum. “ZAYAN: Disentangled Contrastive Transformer for Tabular Remote Sensing Data.” In Proceedings of the 28th ...
GitHub

Disentangled Contrastive Collaborative Filtering

In this paper, we propose a disentangled contrastive learning method for recommendation, which explores latent factors underlying implicit intents for interactions. In particular, a graph structure ...