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20242026
most citedFredformer: Frequency Debiased Transformer for Time Series Forecasting

108 citations · 111 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.LG2026

Optimizing EEG Graph Structure for Seizure Detection: An Information Bottleneck and Self-Supervised Learning Approach

Lincan Li, Rikuto Kotoge, Xihao Piao +2

Seizure detection from EEG signals is highly challenging due to complex spatiotemporal dynamics and extreme inter-patient variability. To model them, recent methods construct dynam…

cs.LG2026

TIFO: Time-Invariant Frequency Operator for Stationarity-Aware Representation Learning in Time Series

Xihao Piao, Zheng Chen, Lingwei Zhu +3

Nonstationary time series forecasting suffers from the distribution shift issue due to the different distributions that produce the training and test data. Existing methods attempt…

cs.LG2025

Tokenizing Single-Channel EEG with Time-Frequency Motif Learning

Jathurshan Pradeepkumar, Xihao Piao, Zheng Chen +1

Foundation models are reshaping EEG analysis, yet an important problem of EEG tokenization remains a challenge. This paper presents TFM-Tokenizer, a novel tokenization framework th…

cs.LG2024★ 1 cited

A Unified Energy Management Framework for Multi-Timescale Forecasting in Smart Grids

Dafang Zhao, Xihao Piao, Zheng Chen +2

Accurate forecasting of the electrical load, such as the magnitude and the timing of peak power, is crucial to successful power system management and implementation of smart grid s…

cs.LG2024★ 108 cited

Fredformer: Frequency Debiased Transformer for Time Series Forecasting

Xihao Piao, Zheng Chen, Taichi Murayama +2

The Transformer model has shown leading performance in time series forecasting. Nevertheless, in some complex scenarios, it tends to learn low-frequency features in the data and ov…