108 citations · 111 across the 7 of their papers we have counts for
9 papers
Do Self-Evolving Skills Generalize to Held-Out Tasks?
Xihao Piao, Zifeng Wang, Zhen Chen
AI agents can externalize what they learn from past tasks into reusable \emph{skills}, such as procedures, checklists, code, or other executable artifacts, that can be retrieved an…
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…
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…
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…
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…
FredNormer: Frequency Domain Normalization for Non-stationary Time Series Forecasting
Xihao Piao, Zheng Chen, Yushun Dong +2
Recent normalization-based methods have shown great success in tackling the distribution shift issue, facilitating non-stationary time series forecasting. Since these methods opera…
BernGraph: Probabilistic Graph Neural Networks for EHR-based Medication Recommendations
Xihao Piao, Pei Gao, Zheng Chen +4
The medical community believes binary medical event outcomes in EHR data contain sufficient information for making a sensible recommendation. However, there are two challenges to e…
MLOmics: Cancer Multi-Omics Database for Machine Learning
Ziwei Yang, Rikuto Kotoge, Xihao Piao +6
Framing the investigation of diverse cancers as a machine learning problem has recently shown significant potential in multi-omics analysis and cancer research. Empowering these su…
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…