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20222026
most citedTEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series

20 citations · 38 across the 18 of their papers we have counts for

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12 papers · 1 filter

cs.LG2026

EchoBridge: Long-Tail-Aware ECG-Echocardiography Text Alignment for Echocardiography-Derived Cardiac Findings

Xiaocheng Fang, Jieyi Cai, Guangkun Nie +9

Standardized echocardiography conclusions provide meaningful supervision for learning ECG representations of echocardiography-derived cardiac findings. Global ECG--text alignment m…

cs.LG2026

ImputeECG: Deep Learning Reconstruction of Complete 12-Lead Electrocardiograms from Incomplete Recordings for Cardiac Assessment

Xiaocheng Fang, Haoyu Wang, Jieyi Cai +14

Complete digital 12-lead electrocardiograms (ECGs) are essential for AI-enabled cardiovascular assessment, yet many clinical ECG records, particularly those digitized from ECG imag…

cs.LG2026

CausalMoE: A Billion-Scale Multimodal Foundation Model for Granger Causal Discovery with Pattern-Routed Heterogeneous Experts

Bo Liu, Di Dai, Jingwei Liu +5

Granger Causal Discovery (GCD) is fundamental for analyzing temporal dependencies in complex systems. However, existing neural GCD methods predominantly rely on a "one-size-fits-al…

cs.LG2025

PPGFlowECG: Latent Rectified Flow with Cross-Modal Encoding for PPG-Guided ECG Generation and Cardiovascular Disease Detection

Xiaocheng Fang, Jiarui Jin, Haoyu Wang +8

Electrocardiography (ECG) is the clinical gold standard for cardiovascular disease (CVD) assessment, yet continuous monitoring is constrained by the need for dedicated hardware and…

cs.LG2025

ECGTwin: Personalized ECG Generation Using Controllable Diffusion Model

Yongfan Lai, Bo Liu, Xinyan Guan +3

Personalized electrocardiogram (ECG) generation is to simulate a patient's ECG digital twins tailored to specific conditions. It has the potential to transform traditional healthca…

cs.LG2025★ 1 cited

Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model

Jiarui Jin, Haoyu Wang, Hongyan Li +3

Electrocardiogram (ECG) is essential for the clinical diagnosis of arrhythmias and other heart diseases, but deep learning methods based on ECG often face limitations due to the ne…

cs.LG2025★ 8 cited

DiffuSETS: 12-lead ECG Generation Conditioned on Clinical Text Reports and Patient-Specific Information

Yongfan Lai, Jiabo Chen, Deyun Zhang +4

Heart disease remains a significant threat to human health. As a non-invasive diagnostic tool, the electrocardiogram (ECG) is one of the most widely used methods for cardiac screen…

cs.LG2024★ 1 cited

Retrieval-Augmented Diffusion Models for Time Series Forecasting

Jingwei Liu, Ling Yang, Hongyan Li +1

While time series diffusion models have received considerable focus from many recent works, the performance of existing models remains highly unstable. Factors limiting time series…

cs.LG2024★ 1 cited

Review of Data-centric Time Series Analysis from Sample, Feature, and Period

Chenxi Sun, Hongyan Li, Yaliang Li +1

Data is essential to performing time series analysis utilizing machine learning approaches, whether for classic models or today's large language models. A good time-series dataset…

cs.LG2023

Curricular and Cyclical Loss for Time Series Learning Strategy

Chenxi Sun, Hongyan Li, Moxian Song +2

Time series widely exists in real-world applications and many deep learning models have performed well on it. Current research has shown the importance of learning strategy for mod…

cs.LG2022★ 2 cited

Continuous Diagnosis and Prognosis by Controlling the Update Process of Deep Neural Networks

Chenxi Sun, Hongyan Li, Moxian Song +3

Continuous diagnosis and prognosis are essential for intensive care patients. It can provide more opportunities for timely treatment and rational resource allocation, especially fo…

cs.LG2022★ 4 cited

Confidence-Guided Learning Process for Continuous Classification of Time Series

Chenxi Sun, Moxian Song, Derun Can +3

In the real world, the class of a time series is usually labeled at the final time, but many applications require to classify time series at every time point. e.g. the outcome of a…