Cover Image

Multivariate Time Series Data Imputation via Distributionally Robust Regularization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liao, Che-Yi, Dong, Zheng, Garcia, Gian-Gabriel, Paynabar, Kamran
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Applications
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Tides Need STEMMED: A Locally Operating Spatio-Temporal Mutually Exciting Point Process with Dynamic Network for Improving Opioid Overdose Death Prediction
by: Liao, Che-Yi, et al.
Published: (2022)

Robust Spectral Fuzzy Clustering of Multivariate Time Series with Applications to Electroencephalogram
by: Ma, Ziling, et al.
Published: (2025)

Demand Forecasting for Platelet Usage: from Univariate Time Series to Multivariate Models
by: Motamedi, Maryam, et al.
Published: (2021)

MMformer with Adaptive Transferable Attention: Advancing Multivariate Time Series Forecasting for Environmental Applications
by: Xin, Ning, et al.
Published: (2025)

Multilevel Stochastic Optimization for Imputation in Massive Medical Data Records
by: Li, Wenrui, et al.
Published: (2021)

Discovery of Generalizable TBI Phenotypes Using Multivariate Time-Series Clustering
by: Ghaderi, Hamid, et al.
Published: (2024)

Modeling Information Blackouts in Missing Not-At-Random Time Series Data
by: Sunesh, Aman, et al.
Published: (2026)

Visually Evaluating Generative Adversarial Networks Using Itself under Multivariate Time Series
by: Pan, Qilong
Published: (2022)

Predictive Uncertainty in Short-Term PV Forecasting under Missing Data: A Multiple Imputation Approach
by: Pashmchi, Parastoo, et al.
Published: (2026)

Online Multivariate Regularized Distributional Regression for High-dimensional Probabilistic Electricity Price Forecasting
by: Hirsch, Simon
Published: (2025)

Learning-to-Defer in Non-Stationary Time Series via Switching State-Space Models
by: Montreuil, Yannis, et al.
Published: (2026)

Deep Autocorrelation Modeling for Time-Series Forecasting: Progress and Prospects
by: Wang, Hao, et al.
Published: (2026)

Active Region-based Flare Forecasting with Sliding Window Multivariate Time Series Forest Classifiers
by: Ji, Anli, et al.
Published: (2024)

Optimal Sampling Designs for Multi-dimensional Streaming Time Series with Application to Power Grid Sensor Data
by: Xie, Rui, et al.
Published: (2023)

Integrating Response Time and Attention Duration in Bayesian Preference Learning for Multiple Criteria Decision Aiding
by: Jiang, Jiaxuan, et al.
Published: (2025)

Efficient Causal Discovery for Autoregressive Time Series
by: Fesanghary, Mohammad, et al.
Published: (2025)

Which Imputation Fits Which Feature Selection Method? A Survey-Based Simulation Study
by: Schwerter, Jakob, et al.
Published: (2024)

Time-Series Anomaly Classification for Launch Vehicle Propulsion Systems: Fast Statistical Detectors Enhancing LSTM Accuracy and Data Quality
by: Engelstad, Sean P., et al.
Published: (2026)

Evaluating Imputation Techniques for Short-Term Gaps in Heart Rate Data
by: Gupta, Vaibhav, et al.
Published: (2025)

Structured Matching via Cost-Regularized Unbalanced Optimal Transport
by: Pardini, Emanuele, et al.
Published: (2025)

Copula Conformal Prediction for Multi-step Time Series Forecasting
by: Sun, Sophia, et al.
Published: (2022)

Variable Selection Methods for Multivariate, Functional, and Complex Biomedical Data in the AI Age
by: Matabuena, Marcos
Published: (2025)

An Agglomerative Clustering of Simulation Output Distributions Using Regularized Wasserstein Distance
by: Ghasemloo, Mohammadmahdi, et al.
Published: (2024)

Robust Distributed Estimation: Extending Gossip Algorithms to Ranking and Trimmed Means
by: Van Elst, Anna, et al.
Published: (2025)

Informed Forecasting: Leveraging Auxiliary Knowledge to Boost LLM Performance on Time Series Forecasting
by: Ghasemloo, Mohammadmahdi, et al.
Published: (2025)

ACT-Tensor: Tensor Completion Framework for Financial Dataset Imputation
by: Mo, Junyi, et al.
Published: (2025)

Missing Data Imputation With Granular Semantics and AI-driven Pipeline for Bankruptcy Prediction
by: Chakraborty, Debarati, et al.
Published: (2024)

Enhancing Interpretability and Generalizability in Extended Isolation Forests
by: Arcudi, Alessio, et al.
Published: (2023)

Deep Switching State Space Model (DS$^3$M) for Nonlinear Time Series Forecasting with Regime Switching
by: Xu, Xiuqin, et al.
Published: (2021)

Zero-inflation in the Multivariate Poisson Lognormal Family
by: Batardière, Bastien, et al.
Published: (2024)

Adaptive Norm-Based Regularization for Neural Networks
by: Qasim, Muhammad, et al.
Published: (2026)

A Composite-Loss Graph Neural Network for the Multivariate Post-Processing of Ensemble Weather Forecasts
by: Lakatos, Mária
Published: (2025)

Starting Off on the Wrong Foot: Pitfalls in Data Preparation
by: Guo, Jiayi, et al.
Published: (2026)

Regularized Multi-output Gaussian Convolution Process with Domain Adaptation
by: Xinming, Wang, et al.
Published: (2024)

DRL-STAF: A Deep Reinforcement Learning Framework for State-Aware Forecasting of Complex Multivariate Hidden Markov Processes
by: Jiang, Manrui, et al.
Published: (2026)

Analyzing the Impact of Climate Change With Major Emphasis on Pollution: A Comparative Study of ML and Statistical Models in Time Series Data
by: Mishra, Anurag, et al.
Published: (2024)

Bayesian Multivariate Density-Density Regression
by: Nguyen, Khai, et al.
Published: (2025)

Multi-View Variational Autoencoder for Missing Value Imputation in Untargeted Metabolomics
by: Zhao, Chen, et al.
Published: (2023)

Assessing the Operational Viability of Foundation Models for Time Series Forecasting
by: Soni, Kavin, et al.
Published: (2026)

Context-Alignment: Activating and Enhancing LLM Capabilities in Time Series
by: Hu, Yuxiao, et al.
Published: (2025)