Temporal Dependence

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43 papers

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Neural ODE enhanced linear mixed effect models for estimating complex association patterns of time-varying covariates with the marker trajectory
Aug 30, 2026Zhe Aurore Li, Quentin Clairon, Cécilia Samieri +3Neural Ordinary Differential Equations Covariate Shift
HSTGFormer: Hyper Spatial-Temporal Graph Transformer for 3D Human Pose Estimation
Aug 12, 2026Ruochen Li, Shuang Chen, Wenke E +23D Pose Estimator Spatio-Temporal Transformers
JAPE: Joint Anomaly Prediction and Intrinsic Explanation in Multivariate Time Series
Aug 12, 2026Yian Wei, Yuanyuan Yao, Lu Chen +2Time-Series Anomaly Detection Anomaly Detection
Recurrent Neural Networks Beyond Time: Learning from Multiple Ordered Projections
Aug 10, 2026Vagan Terziyan, Artur Terziian, Oleksandra VitkoRecurrent Neural Networks Sequence Modeling
GeoID-PINN: Identifiability-Aware Regional Epidemic Inference with Geographic Coupling
Jul 28, 2026Weixiong Hua, Fan BuEpidemic Forecasting Temporal Dependence
GTIN: A Unified Framework for Joint Event and Time Prediction in Temporal Graphs
Jul 26, 2026Mohammad Ostadmohammadi, Sepehr Kazemi, Hamid R. RabieeTemporal Graphs Temporal Dependence
VGIF-Score: Interpretable and Diagnostic Evaluation of Spatio-Temporal Instruction Following in Video Generation
Jul 15, 2026Songyu Xu, Xin Wang, Qiang Chen +6Instruction Temporal Dependence
Social-spatial dependencies for learning visual navigation
Jul 8, 2026Patrick Govoni, Pawel RomanczukSocial Dynamics Navigation
Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing
Jun 30, 2026Eric Shen, Tony Wu, Mahbod Majid +1Conditional Independence Temporal Dependence
Doubly Robust Adaptive Conformal Inference for Causal Effects Under Temporal Dependence
Jun 29, 2026Andreas Koukorinis, Ricardo SilvaCausal Inferences Conformal Inference
OWMDrive: Causality-Aware End-to-End Autonomous Driving via 4D Occupancy World Model
Jun 29, 2026Junjie Cheng, Ruiqi Song, Ye Wu +3Autonomous Driving Trajectory Prediction
Global Explanations for Multivariate Time Series Forecasting Models via $K$ -Order Markov ApproximationsGlobal Explanations for Multivariate Time Series Forecasting Models via K-Order Markov Approximations
Jun 25, 2026Amadeo TunyiMultivariate Forecasting Multivariate Time Series Forecasting
GRACE: Gated Refinement for Accurate Causal Edge Discovery in High-Dimensional Time Series
Jun 22, 2026Mohammad Fesanghary, Abhinav HavaldarCausal Foundation Models Temporal Dependence
Statistical Matching via Schrödinger Bridge beyond Conditional Independence
Jun 22, 2026Eunho Koo, Tongseok Lim, Jinwon SohnImputation Schrödinger Bridges
Temporal Causal Prior-Data Fitted Networks for Panel Data with Learned Reliability Signals
Jun 18, 2026Shravan Talupula, Saurabh SharmaCausal Foundation Models Tabular Prior-Data Fitted Network
From Coarse to Fine: Managing Temporal Granularity in Spatio-Temporal Data for Fine-Grained Traffic Prediction
Jun 8, 2026Shuhao Li, Weidong Yang, Yue Cui +4Accurate Traffic Forecasting Spatiotemporal
Diffusion Models for Adaptive Sequential Data Generation
Jun 4, 2026Haoyang Cao, Minshuo Chen, Yinbin Han +1Synthetic Time Series Discrete Diffusion Model
Learning Temporal Causal Structure via Smooth Differentiable Optimization
Jun 2, 2026Tong Zhao, Ce Guo, Wayne Luk +2Causal Foundation Models Temporal Dependence
Estimating Mutual Information between Time Series and Temporal Event Sequences Across Diverse Analysis Tasks
Jun 1, 2026Haoji Hu, Huaqing Mao, Yijun Lin +4Temporal Dependence Time Series
AdaKernel: Learning Adaptive Kernel Parameters for Spatiotemporal Graph Neural Networks
May 31, 2026Zhongyue Zhang, Guangyin Jin, Yuxuan Liang +2Graph Neural Networks Kernel Method
InfoAtlas: A Foundation Model for Zero-Shot Statistical Dependence Estimate
May 29, 2026Zhengyang Hu, Yanzhi Chen, Hanxiang Ren +5Mutual Information Temporal Dependence
Identifying Explicit Parsimonious Piece-wise Polynomial Relationships in Industrial time-series: Application to manipulator robots
May 27, 2026Mazen Alamir, Sacha ClavelSystem Identification Robotic Arms
Generative Spatiotemporal Intent Sequence Recommendation via Implicit Reasoning in Amap
May 27, 2026Sicong Wang, Ruiting Dong, Yue Liu +7Large Language Model Planning Large-Scale Recommendation Systems
Time Series Causal Discovery via Context-Conditioned and Causality-Augmented Pretraining
May 26, 2026Biao Ouyang, Tengxue Zhang, Zhihao Zhuang +3Causal Foundation Models Temporal Dependence
PHGNet: Prototype-Guided Hypergraph Construction for Heterogeneous Spatiotemporal Forecasting
May 25, 2026Ruiwen Gu, Yahao Liu, Zhenyu Liu +2Accurate Traffic Forecasting Spatio-Temporal Forecasting
A Unified Framework for Structure-Aware Clustering and Heterogeneous Causal Graph Learning
May 19, 2026Honglin Du, Muxuan Liang, Xiang ZhongCausal Graph Directed Acyclic Graph
XCTFormer: Leveraging Cross-Channel and Cross-Time Dependencies for Enhanced Time-Series Analysis
May 18, 2026Israel Zexer, Omri AzencotMultivariate Time Series Forecasting Temporal Dependence
Structured Neural Marked Point Processes for Interpretable Event Interaction Modeling
May 17, 2026Zhitong Xu, Qiwei Yuan, Yinghao Chen +2Determinantal Point Process Temporal Dependence
A Distribution Matching Approach to Neural Piano Transcription with Optimal Transport
May 17, 2026Weixing Wei, Raynaldi Lalang, Dichucheng Li +1Piano Transcription
SeesawNet: Towards Non-stationary Time Series Forecasting with Balanced Modeling of Common and Specific Dependencies
May 14, 2026Hao Li, Lu Zhang, Liu Chong +3Multivariate Time Series Forecasting Non-Stationarity
iPay: Integrated Payment Action Recognition via Multimodal Networks and Adaptive Spatial Prior Learning
May 11, 2026Kaicong Huang, Weiheng Oh, Thomas Guggisberg +1Payment Networks Motion-Focused Representations
VIMCAN: Visual-Inertial 3D Human Pose Estimation with Hybrid Mamba-Cross-Attention Network
May 8, 2026Zepeng Yang, Junxuan Bai, Hao Li +43D Pose Estimator Spatio-Temporal Transformers
Mask2Cause: Causal Discovery via Adjacency Constrained Causal Attention
May 8, 2026Omar Muhammad, Pasupuleti Dhruv Shivkant, Deepak N. SubramaniCausal Foundation Models Causal Attention
Beyond the Independence Assumption: Finite-Sample Guarantees for Deep Q-Learning under $τ$ -MixingBeyond the Independence Assumption: Finite-Sample Guarantees for Deep Q-Learning under τ-Mixing
May 7, 2026Leon Halgryn, Sophie Langer, Janusz M. Meylahn +1Deep Q-Networks Learning Dynamics
R2H-Diff: Guided Spectral Diffusion Model for RGB-to-Hyperspectral Reconstruction
May 7, 2026Songyu Ding, Ronggiang Zhao, Mingchun Sun +1Hyperspectral Imaging Spectral Reconstruction
Dynamic Vine Copulas: Detecting and Quantifying Time-Varying Higher-Order Interactions
May 4, 2026Houman Safaai, Alessandro Marin VargasGaussian Copula Temporal Dependence
TemPose-TF-ASF: Two-Stage Bidirectional Stroke Context Fusion for Badminton Stroke Classification
May 4, 2026Tzu-Yu Liu, Duan-Shin LeeBadminton Multimodal Fusion
TTCD:Transformer Integrated Temporal Causal Discovery from Non-Stationary Time Series Data
Apr 27, 2026Omar Faruque, Sahara Ali, Xue Zheng +1Causal Foundation Models Non-Stationarity
GAMMA-Net: Adaptive Long-Horizon Traffic Spatio-Temporal Forecasting Model based on Interleaved Graph Attention and Multi-Axis Mamba
Apr 18, 2026Dongyi He, Yuanquan Gao, Bin Jiang +1Accurate Traffic Forecasting Temporal Dependence
Evaluating Temporal and Structural Anomaly Detection Paradigms for DDoS Traffic
Apr 17, 2026Yasmin Souza Lima, Rodrigo Moreira, Larissa F. Rodrigues Moreira +2Denial-Of-Service Attacks Temporal Dependence
Fun-TSG: A Function-Driven Multivariate Time Series Generator with Variable-Level Anomaly Labeling
Apr 14, 2026Pierre Lotte, André Péninou, Olivier TesteTime-Series Anomaly Detection Synthetic Time Series
Few-Shot Demonstration-Driven Task Coordination and Trajectory Execution for Multi-Robot Systems
Oct 17, 2025Taehyeon Kim, Vishnunandan L. N. Venkatesh, Byung-Cheol MinMulti-Robot Systems Robot Trajectories
DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting
Aug 3, 2025Haonan Yang, Jianchao Tang, Zhuo Li +1Multiscale Temporal Dependence

Aug 30, 2026 · stat.MLJ/K move · Enter open · S save

Neural ODE enhanced linear mixed effect models for estimating complex association patterns of time-varying covariates with the marker trajectory

Zhe Aurore Li, Quentin Clairon, Cécilia Samieri, Rodolphe Thiébaut+2

Univ. Bordeaux, Inserm, BPH, UMR 1219, 33000 Bordeaux, France · INRIA SISTM, 33000 Bordeaux, France · Vaccine Research Institute, 94010 Creteil, France

Longitudinal cohort studies produce repeated data that enable the assessment of time-varying association patterns between exposures and health outcomes. Classical linear mixed-effects models (LMMs) can accommodate a large variety of association patterns while accounting for the irregularly spaced, partially observed measurement. But they require the analyst to pre-specify the functional form linking the exposure history to the outcome. We propose the Neural ODE-LMM, which embeds a Neural Ordinary Differential Equation (Neural ODE) within the linear mixed-effects framework: a learned vector field encodes covariate trajectories into a continuous-time latent state that drives both the fixed- and random-effect design, while preserving the standard LMM observation model. This retains classical likelihood-based inference while learning complex, potentially cumulative, covariate effects flexibly. All parameters are estimated by maximising a penalised marginal likelihood. To quantify covariate effects, we introduce contrasts of counterfactual predictions that compare the expected outcome under alternative covariate trajectories with variance estimated via the delta method. In simulations, the model recovers both instantaneous and cumulative-burden effects without prior specification of the functional form. Applied to the Trois-Cités (3C) cohort, a population-based study of 7{,}324 participants, the method reveals trajectory-dependent associations of BMI and fasting glucose with cognitive decline.

Neural Ordinary Differential Equations Covariate Shift Logistic Regression Longitudinal Data Temporal Dependence Trajectory Prediction

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