Image de couverture de livre

ECG Latent Feature Extraction with Autoencoders for Downstream Prediction Tasks

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Harvey, Christopher, Shomaji, Sumaiya, Yao, Zijun, Noheria, Amit
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Comparison of Autoencoder Encodings for ECG Representation in Downstream Prediction Tasks
par: Harvey, Christopher J., et autres
Publié: (2024)

ILASH: A Predictive Neural Architecture Search Framework for Multi-Task Applications
par: Rahman, Md Hafizur, et autres
Publié: (2024)

Panprediction: Optimal Predictions for Any Downstream Task and Loss
par: Balakrishnan, Sivaraman, et autres
Publié: (2025)

An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reduction
par: Liang, Yaxin, et autres
Publié: (2024)

Exploring the Impact of a Transformer's Latent Space Geometry on Downstream Task Performance
par: Marbut, Anna C., et autres
Publié: (2024)

Quasiparticle Interference Kernel Extraction with Variational Autoencoders via Latent Alignment
par: Ji, Yingshuai, et autres
Publié: (2025)

Fairness-Optimized Synthetic EHR Generation for Arbitrary Downstream Predictive Tasks
par: Tarek, Mirza Farhan Bin, et autres
Publié: (2024)

Downstream Task Guided Masking Learning in Masked Autoencoders Using Multi-Level Optimization
par: Guo, Han, et autres
Publié: (2024)

Principled Latent Diffusion for Graphs via Laplacian Autoencoders
par: Siraudin, Antoine, et autres
Publié: (2026)

Smoke and Mirrors in Causal Downstream Tasks
par: Cadei, Riccardo, et autres
Publié: (2024)

Rethinking the Starting Point: Collaborative Pre-Training for Federated Downstream Tasks
par: Chu, Yun-Wei, et autres
Publié: (2024)

ECGXtract: Deep Learning-based ECG Feature Extraction for Automated CVD Diagnosis
par: Abuzied, Youssif, et autres
Publié: (2025)

Mixing Configurations for Downstream Prediction
par: Wang, Juntang, et autres
Publié: (2025)

Hybrid Gaussian Process Regression with Temporal Feature Extraction for Partially Interpretable Remaining Useful Life Interval Prediction in Aeroengine Prognostics
par: Niu, Tian, et autres
Publié: (2024)

Learning Interpretable Features in Audio Latent Spaces via Sparse Autoencoders
par: Paek, Nathan, et autres
Publié: (2025)

Dataset Representativeness and Downstream Task Fairness
par: Borza, Victor, et autres
Publié: (2024)

In-ear ECG Signal Enhancement with Denoising Convolutional Autoencoders
par: Occhipinti, Edoardo, et autres
Publié: (2024)

Analogue Forecast System for Daily Precipitation Prediction Using Autoencoder Feature Extraction: Application in Hong Kong
par: Tsoi, Yee Chun, et autres
Publié: (2025)

Disentangling Genotype and Environment Specific Latent Features for Improved Trait Prediction using a Compositional Autoencoder
par: Powadi, Anirudha, et autres
Publié: (2024)

Handling Missing Data in Downstream Tasks With Distribution-Preserving Guarantees
par: Bordoloi, Rahul, et autres
Publié: (2025)

Aligning the Evaluation of Probabilistic Predictions with Downstream Value
par: Shahroudi, Novin, et autres
Publié: (2025)

Sculpting Features from Noise: Reward-Guided Hierarchical Diffusion for Task-Optimal Feature Transformation
par: Gong, Nanxu, et autres
Publié: (2025)

Masked Autoencoders for Ultrasound Signals: Robust Representation Learning for Downstream Applications
par: Roßteutscher, Immanuel, et autres
Publié: (2025)

Attacking Attention of Foundation Models Disrupts Downstream Tasks
par: Silva, Hondamunige Prasanna, et autres
Publié: (2025)

Towards a Unified Representation Evaluation Framework Beyond Downstream Tasks
par: Plachouras, Christos, et autres
Publié: (2025)

Pretraining Induces a Reusable Spectral Basis for Downstream Task Adaptation
par: Yu, Junjie, et autres
Publié: (2026)

Task-tailored Pre-processing: Fair Downstream Supervised Learning
par: Sohn, Jinwon, et autres
Publié: (2026)

Scalable Feature Learning on Huge Knowledge Graphs for Downstream Machine Learning
par: Lefebvre, Félix, et autres
Publié: (2025)

CNN Autoencoders for Hierarchical Feature Extraction and Fusion in Multi-sensor Human Activity Recognition
par: Arabzadeh, Saeed, et autres
Publié: (2025)

VAE-MS: An Asymmetric Variational Autoencoder for Mutational Signature Extraction
par: Egendal, Ida, et autres
Publié: (2026)

WxC-Bench: A Novel Dataset for Weather and Climate Downstream Tasks
par: Shinde, Rajat, et autres
Publié: (2024)

Task Priors: Enhancing Model Evaluation by Considering the Entire Space of Downstream Tasks
par: Patel, Niket, et autres
Publié: (2025)

Sparse Autoencoder Decomposition of Clinical Sequence Model Representations: Feature Complexity, Task Specialisation, and Mortality Prediction
par: Sainsbury, Chris, et autres
Publié: (2026)

DSAI: Unbiased and Interpretable Latent Feature Extraction for Data-Centric AI
par: Cho, Hyowon, et autres
Publié: (2024)

Harvesting AlphaEarth: Benchmarking the Geospatial Foundation Model for Agricultural Downstream Tasks
par: Ma, Yuchi, et autres
Publié: (2025)

Scaling Laws Are Unreliable for Downstream Tasks: A Reality Check
par: Lourie, Nicholas, et autres
Publié: (2025)

On the Impact of Downstream Tasks on Sampling and Reconstructing Noisy Graph Signals
par: Sripathmanathan, Baskaran, et autres
Publié: (2025)

Scaling Laws for Downstream Task Performance of Large Language Models
par: Isik, Berivan, et autres
Publié: (2024)

Multi-Task LLM with LoRA Fine-Tuning for Automated Cancer Staging and Biomarker Extraction
par: Shao, Jiahao, et autres
Publié: (2026)

VARAN: Variational Inference for Self-Supervised Speech Models Fine-Tuning on Downstream Tasks
par: Diatlova, Daria, et autres
Publié: (2025)