Missing Data

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Period ending 2026-09-21

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Period ending 2026-09-14

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Missing Data

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Imputation

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Multivariate Time Series Imputation

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103 papers

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MambaGaze: Bidirectional Mamba with Explicit Missing Data Modeling for Cognitive Load Assessment from Eye-Gaze Tracking Data
May 21, 2026Amir Mousavi, Mohammad Sadegh Sirjani, Erfan Nourbakhsh +5Eye Tracking Cognitive Load
StruMPL: Multi-task Dense Regression under Disjoint Partial Supervision and MNAR Labels
May 19, 2026Reza M. Asiyabi, Juan Alberto Molina-Valero, The SEOSAW Partnership +2Above-Ground Biomass Logistic Regression
Increasing Missingness to Reduce Bias: Richardson-SGD with Missing Data
May 19, 2026Ferdinand Genans, Erwan ScornetMissing Data Imputation
Remote sensing data imputation using deep learning for multispectral imagery
May 19, 2026Shuang Liu, Fiona Johnson, Rohitash ChandraSatellite Data Imputation
Can Large Language Models Revolutionize Survey Research? Experiments with Disaster Preparedness Responses
May 19, 2026Yan Wang, Ziyi Guo, Christopher McCartySurvey Large Language
Learning Higher-Order Structure from Incomplete Spatiotemporal Data: Multi-Scale Hypergraph Laplacians with Neural Refinement
May 17, 2026Keshu Wu, Sixu Li, Zihao Li +3Hypergraphs Imputation
Federated Imputation under Heterogeneous Feature Spaces
May 15, 2026Imane Hocine, Chaimaa Medjadji, Sylvain Kubler +2Federated Learning Imputation
LLMs as Implicit Imputers: Uncertainty Should Scale with Missing Information
May 13, 2026Stef van BuurenLarge Language Model Uncertainty Multivariate Time Series Imputation
PRA-PoE: Robust Multimodal Alzheimer's Diagnosis with Arbitrary Missing Modalities
May 13, 2026Guangqian Yang, Ye Du, Wenlong Hou +2Missing Modalities Robust Multimodal Learning
Quantifying Potential Observation Missingness in Inverse Reinforcement Learning
May 12, 2026Leo Benac, Abhishek Sharma, Alihan Huyuk +1Entropy Regularized Reinforcement Learning Missing Data
Missingness-MDPs: Bridging the Theory of Missing Data and POMDPs
May 12, 2026Joshua Wendland, Markel Zubia, Roman Andriushchenko +6Partially Observable Markov Decision Process Missing Data
Latent Causal Void: Explicit Missing-Context Reconstruction for Misinformation Detection
May 12, 2026Hui Li, Zhongquan Jian, Jinsong Su +1Misinformation Detection Natural Language Inference
U-STS-LLM A Unified Spatio-Temporal Steered Large Language Model for Traffic Prediction and Imputation
May 12, 2026Yichen Zhang, Jun LiTemporal Graph Neural Networks Imputation
OverNaN: NaN-Aware Oversampling for Imbalanced Learning with Meaningful Missingness
May 12, 2026Amanda S BarnardOversampling Missing Data
Augmenting Human Evaluation with LLM Judges: How Many Human Reviews Do You Need?
May 8, 2026Jane Paik KimLarge Language Model Evaluation Large Language Model Judges
Future Validity is the Missing Statistic: From Impossibility to $Φ$ -Estimation for Grammar-Faithful Speculative Decoding
May 8, 2026Wenhua Nie, Zijie Meng, Kun Zou +5Speculative Decoding Context-Free Grammars
Order-Agnostic Autoregressive Modelling with Missing Data
May 7, 2026Ignacio Peis, Pablo M. Olmos, Jes FrellsenMissing Data Imputation
Temporal Smoothness Doubly Robust Learning for Debiased Knowledge Tracing
May 7, 2026Peilin Zhan, Wei Chen, Weilin Chen +2Per-Competency Bayesian Knowledge Tracing Trajectory-Aware Differential Aggregation
AirQualityBench: A Realistic Evaluation Benchmark for Global Air Quality Forecasting
May 7, 2026Xing Xu, Xu Wang, Yudong Zhang +3Air Pollution Evaluation Benchmarks
PAIR-CI: Calibrated Conditional Independence Testing for Causal Discovery with Incomplete Data
May 6, 2026Thomas S. Robinson, Ranjit LallConditional Independence Multivariate Time Series Imputation
Predicting missing values: A good idea?
May 5, 2026Stef van BuurenMultivariate Time Series Imputation Missing Data
HELIX: Hybrid Encoding with Learnable Identity and Cross-dimensional Synthesis for Time Series Imputation
May 4, 2026Fengming Zhang, Wenjie Du, Huan Zhang +2Imputation Attention-Based Models
Submodular Benchmark Selection
May 4, 2026Alexander SmolaSubmodular Maximization Benchmarking Large Language Models
Missingness-aware Data Imputation via AI-powered Bayesian Generative Modeling
May 3, 2026Qiao LiuImputation Missing Data
EmoMM: Benchmarking and Steering MLLM for Multimodal Emotion Recognition under Conflict and Missingness
May 1, 2026Yueru Sun, Yimeng Zhang, Haoyu Gu +5Emotion Recognition Modality Gap
SPLICE: Latent Diffusion over JEPA Embeddings for Conformal Time-Series Inpainting
Apr 30, 2026Arnaud ZinflouMultivariate Time Series Imputation Electricity Price Forecasting
End-to-End Learning for Partially-Observed Time Series with PyPOTS
Apr 27, 2026Wenjie Du, Yiyuan Yang, Tianxiang Zhan +1Missing Data Data Mining
Conditional Imputation for Within-Modality Missingness in Multi-Modal Federated Learning
Apr 25, 2026Wugeng Zheng, Ziwen Kan, Katie Wang +2Missing Modalities Missing Data
Learning Dynamic Representations and Policies from Multimodal Clinical Time-Series with Informative Missingness
Apr 23, 2026Zihan Liang, Ziwen Pan, Ruoxuan XiongMultimodal Clinical Data Robust Multimodal Learning
Expert-Guided Class-Conditional Goodness-of-Fit Scores for Interpretable Classification with Informative Missingness: An Application to Seismic Monitoring
Apr 16, 2026Shahar Cohen, David M. Steinberg, Yael Radzyner +1Missing Data Statistical Models
On the Inherent Privacy Amplification of Missing Data
Feb 2, 2026Simon Roburin, Rafa{ë}l Pinot, Erwan ScornetDifferential Privacy Missing Data
Theoretical Analysis of Measure Consistency Regularization for Partially Observed Data
Feb 1, 2026Yinsong Wang, Shahin ShahrampourRegularization Techniques Imputation
Geometric Stability: The Missing Axis of Representations
Jan 14, 2026Prashant C. RajuSemantic-Geometric Representations Reference-Free Metric
Modeling Information Blackouts in Missing Not-At-Random Time Series Data
Jan 4, 2026Aman Sunesh, Allan Ma, Siddarth NilolAccurate Traffic Forecasting Missing Data
FADTI: Fourier and Attention Driven Diffusion for Multivariate Time Series Imputation
Dec 17, 2025Runze Li, Hanchen Wang, Wenjie Zhang +4Multivariate Time Series Imputation Fourier
Geometry as a Missing Axis of Representation Quality: The Variational Geometric Information Bottleneck under Data Scarcity
Nov 4, 2025Ronald KatendeInformation Bottleneck Generalization Bounds
Linear Regression under Missing or Corrupted Coordinates
Sep 23, 2025Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane +2Corrupted Observations Missing Data
TANDEM: Temporal Attention-guided Neural Differential Equations for Missingness in Time Series Classification
Aug 24, 2025YongKyung Oh, Dong-Young Lim, Sungil Kim +1Time-Series Classification Missing Data
How Reliable are Fairness Audits with Unreliable Data?
Jun 28, 2025Yash Vardhan TomarFairness Audits False Positive Rate
Deep learning with missing data
Apr 21, 2025Tianyi Ma, Tengyao Wang, Richard J. SamworthImputation Nonparametric
Active Exploration via Autoregressive Generation of Missing Data
May 29, 2024Tiffany Tianhui Cai, Hongseok Namkoong, Daniel Russo +1Efficient Exploration Uncertainty-Aware Inference
Interpretable factorization of clinical questionnaires to identify latent factors of psychopathology
Dec 12, 2023Ka Chun Lam, Francisco Pereira, Bridget W Mahony +1Exploratory Factor Analysis Psychometrics
SafeImpute: Reliable Clinical Data Imputation via Conformal Selection
Date pendingXinrui He, Mengting Ai, Junting Wang +2Multivariate Time Series Imputation Imputation

May 21, 2026 · cs.LGJ/K move · Enter open · S save

MambaGaze: Bidirectional Mamba with Explicit Missing Data Modeling for Cognitive Load Assessment from Eye-Gaze Tracking Data

Amir Mousavi, Mohammad Sadegh Sirjani, Erfan Nourbakhsh, Mimi Xie+4

Department of Computer Science, College of AI, Cyber and Computing, The University of Texas at San Antonio · Department of Neuroscience, Developmental and Regenerative Biology, College of Sciences, The University of Texas at San Antonio · Department of Educational Psychology, College of Education and Human Development, The University of Texas at San Antonio

Real-time cognitive load assessment from eye-tracking signals could enable adaptive human-centered AI in safety-critical applications such as driver vigilance monitoring or automated flight deck assistance, yet two challenges persist: handling frequent data missingness from blinks and tracking failures, and efficiently modeling long-range temporal dependencies. We propose MambaGaze (Bi-Mamba), a framework that addresses these challenges through (1)~XMD encoding, which augments raw features with observation masks and time-deltas to explicitly model data uncertainty, and (2)~bidirectional Mamba-2, which captures temporal dependencies with linear computational complexity. Experiments on CLARE and CL-Drive datasets under leave-one-subject-out evaluation show that MambaGaze achieves 77.1% accuracy and 59.2% macro-F1 on CLARE, and 69.4% accuracy and 51.5% macro-F1 on CL-Drive, attaining the highest average LOSO macro-F1 (55.3%) across all ten compared models. Input-stream ablation indicates that log-scaled time-deltas are the strongest single channel in our setting, and combining all three XMD streams provides consistent gains of 5--20,pp macro-F1. Edge deployment benchmarks on three NVIDIA Jetson Orin platforms show real-time inference at 27--36,FPS with power consumption below 6.6,W, supporting feasibility for embedded cognitive load monitoring.

Eye Tracking Cognitive Load Bidirectional Mamba Medmamba Blind Spots Real-Time Inference Trajectory-Aware Differential Aggregation Missing Data

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