Cover Image

Repurposing Foundation Model for Generalizable Medical Time Series Classification

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Huang, Nan, Wang, Haishuai, He, Zihuai, Zitnik, Marinka, Zhang, Xiang
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Adaptive Time Series Reasoning via Segment Selection
by: Messica, Shvat, et al.
Published: (2026)

UniTS: A Unified Multi-Task Time Series Model
by: Gao, Shanghua, et al.
Published: (2024)

Prompting Decision Transformers for Zero-Shot Reach-Avoid Policies
by: Li, Kevin, et al.
Published: (2025)

Ken Utilization Layer: Hebbian Replay Within a Student's Ken for Adaptive Exercise Recommendation
by: Kuling, Grey, et al.
Published: (2025)

Medformer: A Multi-Granularity Patching Transformer for Medical Time-Series Classification
by: Wang, Yihe, et al.
Published: (2024)

An Exploratory Study to Repurpose LLMs to a Unified Architecture for Time Series Classification
by: He, Hansen, et al.
Published: (2026)

Learning Generalized Medical Image Representations through Image-Graph Contrastive Pretraining
by: Khanna, Sameer, et al.
Published: (2024)

Graph Representation Learning in Biomedicine
by: Li, Michelle M., et al.
Published: (2021)

FoldMark: Protecting Protein Generative Models with Watermarking
by: Zhang, Zaixi, et al.
Published: (2024)

Multimodal Medical Code Tokenizer
by: Su, Xiaorui, et al.
Published: (2025)

UnitNorm: Rethinking Normalization for Transformers in Time Series
by: Huang, Nan, et al.
Published: (2024)

A Unified Shape-Aware Foundation Model for Time Series Classification
by: Liu, Zhen, et al.
Published: (2026)

MIRA: Medical Time Series Foundation Model for Real-World Health Data
by: Li, Hao, et al.
Published: (2025)

Graph Adversarial Diffusion Convolution
by: Liu, Songtao, et al.
Published: (2024)

SEMPO: Lightweight Foundation Models for Time Series Forecasting
by: He, Hui, et al.
Published: (2025)

User-friendly Foundation Model Adapters for Multivariate Time Series Classification
by: Feofanov, Vasilii, et al.
Published: (2024)

TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection
by: Li, Mengxuan, et al.
Published: (2024)

PhylaFlow: Hybrid Flow Matching in Billera-Holmes-Vogtmann Tree Space for Phylogenetic Inference
by: Ektefaie, Yasha, et al.
Published: (2026)

PyTDC: A multimodal machine learning training, evaluation, and inference platform for biomedical foundation models
by: Velez-Arce, Alejandro, et al.
Published: (2025)

ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data
by: Li, Mengxuan, et al.
Published: (2025)

Leveraging Generic Time Series Foundation Models for EEG Classification
by: Gnassounou, Théo, et al.
Published: (2025)

Finding Foundation Models for Time Series Classification with a PreText Task
by: Ismail-Fawaz, Ali, et al.
Published: (2023)

Geometric Deep Learning for Structure-Based Drug Design: A Survey
by: Zhang, Zaixi, et al.
Published: (2023)

Federated Foundation Models on Heterogeneous Time Series
by: Chen, Shengchao, et al.
Published: (2024)

Mantis: Lightweight Calibrated Foundation Model for User-Friendly Time Series Classification
by: Feofanov, Vasilii, et al.
Published: (2025)

Distribution-Conditioned Transport
by: Fishman, Nic, et al.
Published: (2026)

Transformers and Their Roles as Time Series Foundation Models
by: Wu, Dennis, et al.
Published: (2025)

Synthetic Series-Symbol Data Generation for Time Series Foundation Models
by: Wang, Wenxuan, et al.
Published: (2025)

CauKer: Classification Time Series Foundation Models Can Be Pretrained on Synthetic Data
by: Xie, Shifeng, et al.
Published: (2025)

How Foundational are Foundation Models for Time Series Forecasting?
by: Karaouli, Nouha, et al.
Published: (2025)

An Efficient and Generalizable Symbolic Regression Method for Time Series Analysis
by: Xie, Yi, et al.
Published: (2024)

Semi-Supervised End-To-End Contrastive Learning For Time Series Classification
by: Cai, Huili, et al.
Published: (2023)

AI Foundation Model for Time Series with Innovations Representation
by: Tong, Lang, et al.
Published: (2025)

Graph Spatiotemporal Process for Multivariate Time Series Anomaly Detection with Missing Values
by: Zheng, Yu, et al.
Published: (2024)

TimeFound: A Foundation Model for Time Series Forecasting
by: Xiao, Congxi, et al.
Published: (2025)

Evaluating Time Series Foundation Models on Noisy Periodic Time Series
by: Gupta, Syamantak Datta
Published: (2025)

MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification
by: Zhang, Da, et al.
Published: (2026)

TiCT: A Synthetically Pre-Trained Foundation Model for Time Series Classification
by: Yeh, Chin-Chia Michael, et al.
Published: (2025)

MedMamba: Recasting Mamba for Medical Time Series Classification
by: He, ZhengXiao, et al.
Published: (2026)

TimesBERT: A BERT-Style Foundation Model for Time Series Understanding
by: Zhang, Haoran, et al.
Published: (2025)