dialect
发表于 2025-3-25 06:27:50
ESSformer: Transformers with ESS Attention for Long-Term Series Forecasting for LTSF: ESSformer. It is built upon two essential components: (i) We adopt the Channel-Patch Independence architecture, where channels share the same model weights and have independent embeddings to avoid the impact of distribution shifts between channels. Patches are used to extract local semant
placebo-effect
发表于 2025-3-25 08:57:10
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LATE
发表于 2025-3-25 12:32:55
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恶名声
发表于 2025-3-25 19:07:19
https://doi.org/10.1007/978-3-031-72347-6artificial intelligence; classification; deep learning; generative models; graph neural networks; image p
漂泊
发表于 2025-3-25 23:28:22
978-3-031-72346-9The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
流利圆滑
发表于 2025-3-26 00:44:07
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FLIRT
发表于 2025-3-26 05:05:23
Mark R. Harrigan M.D.,John P. Deveikis M.D.consistencies in feature spaces, and constraints on downstream tasks. To address these issues, we propose an Adaptive Attention-based Cross-Modal Representation Integration Framework. This framework can adaptively capture and associate feature information from different modalities and effectively al
glisten
发表于 2025-3-26 09:26:27
Mark R. Harrigan M.D.,John P. Deveikis M.D.with multiple videos but are incorrectly labeled as exclusive to ones, leading to numerous incorrectly mismatched data. Furthermore, such ignorance may hinder model performance and flaw the evaluation of video retrieval. To alleviate this problem, we develop a training-free annotation pipeline, Boot
跳脱衣舞的人
发表于 2025-3-26 13:53:45
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美食家
发表于 2025-3-26 20:32:33
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