Imagen de Portada

Time Series Modeling for Heart Rate Prediction: From ARIMA to Transformers

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Ni, Haowei, Meng, Shuchen, Geng, Xieming, Li, Panfeng, Li, Zhuoying, Chen, Xupeng, Wang, Xiaotong, Zhang, Shiyao
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Harnessing Earnings Reports for Stock Predictions: A QLoRA-Enhanced LLM Approach
por: Ni, Haowei, et al.
Publicado: (2024)

When AI Levels the Playing Field: Skill Homogenization, Asset Concentration, and Two Regimes of Inequality
por: Chen, Xupeng, et al.
Publicado: (2026)

Enhancing Exchange Rate Forecasting with Explainable Deep Learning Models
por: Meng, Shuchen, et al.
Publicado: (2024)

Evaluating Modern Approaches in 3D Scene Reconstruction: NeRF vs Gaussian-Based Methods
por: Zhou, Yiming, et al.
Publicado: (2024)

Exploring Diverse Methods in Visual Question Answering
por: Li, Panfeng, et al.
Publicado: (2024)

Artificial Intelligence and Systemic Risk: A Unified Model of Performative Prediction, Algorithmic Herding, and Cognitive Dependency in Financial Markets
por: Meng, Shuchen, et al.
Publicado: (2026)

AI-Driven Alpha Decay: Algorithmic Homogenization, Reflexive Signal Erosion, and the Paradox of Intelligent Markets
por: Meng, Shuchen, et al.
Publicado: (2026)

Test Time Learning for Time Series Forecasting
por: Christou, Panayiotis, et al.
Publicado: (2024)

Auditing Frontier Vision-Language Models for Trustworthy Medical VQA: Grounding Failures, Format Collapse, and Domain Adaptation
por: Chen, Xupeng, et al.
Publicado: (2026)

Predicting Bad Goods Risk Scores with ARIMA Time Series: A Novel Risk Assessment Approach
por: Gond, Bishwajit Prasad
Publicado: (2025)

Enhancing Time Series Forecasting via a Parallel Hybridization of ARIMA and Polynomial Classifiers
por: Nguyen, Thanh Son, et al.
Publicado: (2025)

ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling
por: Chen, Yuqi, et al.
Publicado: (2024)

Interpretable Pre-Trained Transformers for Heart Time-Series Data
por: Davies, Harry J., et al.
Publicado: (2024)

AutoHFormer: Efficient Hierarchical Autoregressive Transformer for Time Series Prediction
por: Zhang, Qianru, et al.
Publicado: (2025)

YZS-model: A Predictive Model for Organic Drug Solubility Based on Graph Convolutional Networks and Transformer-Attention
por: Wang, Chenxu, et al.
Publicado: (2024)

LENS: Large Pre-trained Transformer for Exploring Financial Time Series Regularities
por: Xu, Yuanjian, et al.
Publicado: (2024)

MTS-LOF: Medical Time-Series Representation Learning via Occlusion-Invariant Features
por: Li, Huayu, et al.
Publicado: (2023)

Large Language Model Guided Knowledge Distillation for Time Series Anomaly Detection
por: Liu, Chen, et al.
Publicado: (2024)

Advanced User Credit Risk Prediction Model using LightGBM, XGBoost and Tabnet with SMOTEENN
por: Yu, Chang, et al.
Publicado: (2024)

TIMRL: A Novel Meta-Reinforcement Learning Framework for Non-Stationary and Multi-Task Environments
por: Qi, Chenyang, et al.
Publicado: (2025)

RxnNano:Training Compact LLMs for Chemical Reaction and Retrosynthesis Prediction via Hierarchical Curriculum Learning
por: Li, Ran, et al.
Publicado: (2026)

FHRFormer: A Self-Supervised Masked Transformer Framework for Fetal Heart Rate Time-Series Inpainting and Forecasting
por: Engan, Kjersti, et al.
Publicado: (2026)

Population Aware Diffusion for Time Series Generation
por: Li, Yang, et al.
Publicado: (2025)

Beyond Model Ranking: Predictability-Aligned Evaluation for Time Series Forecasting
por: Feng, Wanjin, et al.
Publicado: (2025)

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

From ARIMA to Attention: Power Load Forecasting Using Temporal Deep Learning
por: Veluru, Suhasnadh Reddy, et al.
Publicado: (2026)

From Chaos to Clarity: Time Series Anomaly Detection in Astronomical Observations
por: Hao, Xinli, et al.
Publicado: (2024)

EDformer: Embedded Decomposition Transformer for Interpretable Multivariate Time Series Predictions
por: Chakraborty, Sanjay, et al.
Publicado: (2024)

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting
por: Yao, Yueyang, et al.
Publicado: (2025)

From Time Series Analysis to Question Answering: A Survey in the LLM Era
por: Li, Wei, et al.
Publicado: (2025)

Towards Lightweight Time Series Forecasting: a Patch-wise Transformer with Weak Data Enriching
por: Wang, Meng, et al.
Publicado: (2025)

AIGC for Industrial Time Series: From Deep Generative Models to Large Generative Models
por: Ren, Lei, et al.
Publicado: (2024)

A Unified Hyperparameter Optimization Pipeline for Transformer-Based Time Series Forecasting Models
por: Xu, Jingjing, et al.
Publicado: (2025)

Rough Transformers for Continuous and Efficient Time-Series Modelling
por: Moreno-Pino, Fernando, et al.
Publicado: (2024)

Deep Learning for Detecting and Early Predicting Chronic Obstructive Pulmonary Disease from Spirogram Time Series
por: Mei, Shuhao, et al.
Publicado: (2024)

Neural Predictive Control to Coordinate Discrete- and Continuous-Time Models for Time-Series Analysis with Control-Theoretical Improvements
por: Li, Haoran, et al.
Publicado: (2025)

A Review of Electromagnetic Elimination Methods for low-field portable MRI scanner
por: Bian, Wanyu, et al.
Publicado: (2024)

Lightweight Time Series Data Valuation on Time Series Foundation Models via In-Context Finetuning
por: Wu, Shunyu, et al.
Publicado: (2025)

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models
por: Ge, Yunfeng, et al.
Publicado: (2025)

TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model
por: Cao, Defu, et al.
Publicado: (2024)