Title：Adversarial Transformer for Multivariate Time Series Forecasting

Abstract：In this presentation, we talk about the multivariate time series forecasting problem using adversarial transformer. A new transformer-based forecasting model, called Fusionformer, is discussed, which includes 1) the introduction of a segment-wise sequence embedding method; 2) the implementation of a fusion attention mechanism; and 3) the development of an adversarial learning method equipped with an auxiliary discriminator to facilitate the learning of data distribution. The proposed Fusionformer is applied to the early warning problem for slope failure in an open-pit mine. Finally, we conclude our main contributions and some future directions.

Speaker：Wang Zidong，Brunel University.

Date：4:30 p.m., 2025-7-27 (Sunday).

Venue: 扬州大学瘦西湖校区数学学院208报告厅

            腾讯会议：219-315-762

Inviter：Liu Yurong

Organizer：School of Mathematical

Students and teachers are welcome.