7 days ago · Time2Vec [19] is a representation learning technique designed to capture temporal patterns in time series data by providing a more expressive representation ...

Aug 25, 2024 · By incorporating Time2Vec embeddings, the model effectively harnesses the temporal information associated with labels. Report issue for preceding element ...

Sep 3, 2024 · The embedding process encodes time, values, variables, and context-target information. We employ the Time2Vec layer (Kazemi et al., 2019) to transform ...

Aug 14, 2024 · This model uses the Time2Vec encoding to transform timestamps to a higher ... Time2vec: Learning a vector representation of time. arXiv preprint arXiv ...

7 days ago · Time2vec: Learning a vector representation of time. (2019). LaiY. et al. Multi-view spatial-temporal enhanced hypergraph network for next poi recommendation.

Aug 26, 2024 · This study proposes ChronoVectors, a novel temporal representation method that addresses these challenges by enabling a more specialized encoding of temporal ...

Aug 24, 2024 · A trajectory is a sequence of timestamped point locations that captures the movement of an object such as a vehicle. Such trajectories encode complex ...

Aug 17, 2024 · By effectively combining Time2Vec, TCN, and Transformer, the proposed model improves the MAPE for forecasting 1–4 days in the future by approximately 7% ...

Aug 22, 2024 · The objective of this paper is to conduct a scientometric analysis of machine learning and deep learning techniques applied to offshore wind energy. The ...

Aug 23, 2024 · This paper presented GTA, a new framework for multivariate time series anomaly detection that involves automatically learning a graph structure, graph ...