NeurIPS 2025PastHealthcare & biologyTime series
NeurIPS 2025 Workshop on Learning from Time Series for Health
TS4H NeurIPS 2025
- Submission deadline
- Sep 3, 2025, 12:00 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (96)
Fetched from OpenReview (v2) on 2026-06-10.
4 Hz, 4 Pages: Just-in-Time Substance Use Relapse Risk Detection from Wearable Time Series Data
A CNN-based Local-Global Self-Attention via Averaged Window Embeddings for Hierarchical ECG Analysis
A novel approach to classification of ECG arrhythmia types with latent ODEs
A Second-Order SpikingSSM for Wearables
A study on intensive care early event prediction: How well do clinicians perform against AI?
A Time Series Foundation Model for Cancer Management
A Time-Series Vision–Language Model for Predicting Progression of Diabetic Retinopathy
ACUMEN: Active Cross-Entropy Method with Uncertainty-driven Neural ODEs for Data-Efficient System Identification in Healthcare
AttentiveGRUAE: An Attention-Based GRU Autoencoder for Temporal Clustering and Behavioral Characterization of Depression from Wearable Data
Autoregressive ConvLSTM Framework for fMRI Time Series Forecasting in Alzheimer’s Disease
Biological Pathway Informed Models with Graph Attention Networks (GAT)
Black Box to Bedside: Distilling Reinforcement Learning for Sepsis Time Series
Blind Source Separation for Fetal PPG with Rate-Based Proxy Supervision
CAND: Cross-Sign Ambiguity Inference for Early Detecting Nuanced Illness Deterioration
CAST: Causal Modeling of Time-Varying Treatment Effects on Head and Neck Cancer
Causal Emergent Representation Learning Under Distribution Shift in Critical Care Time Series
Causal Representation Learning from Multimodal EHRs under Non-Random Modality Missingness
Collective Data Bargaining for Fairness in Health Time Series AI
Computationally Efficient and Generalizable Machine Learning Algorithms for Seizure Detection from EEG Signals
Contrastive Learning for Multi-Label ECG Classification with Jaccard Score–Based Sigmoid Loss
Contrastive Time Series Representation Learning for Neurochemical Concentration Prediction
Convolutional Monge Mapping between EEG Datasets to Support Independent Component Labeling
Decoding Type 2 Diabetes Progression via Metabolic Hormone Time-Series
Don’t Sleep on Sleep Data: Influence of Sleep Physiological Signals on Stress Detection
Dual Mixture-of-Experts Framework for Discrete-Time Survival Analysis
DuLPA: Dual-Level Prototype Alignment for Unsupervised Domain Adaptation in Activity Recognition from Wearables
dynAmiC: Dynamic Domain Adaptation with Efficient Coreset Selection
Early Warning of In-Hospital Cardiac Arrest from Photoplethysmography Using Deep Residual Networks
ECG-MoE: Mixture-of-Expert Electrocardiogram Foundation Model
Estimating Clinical Lab Test Result Trajectories from PPG using Physiological Foundation Model and Patient-Aware State Space Model – a UNIPHY+ Approach
Evaluating Language Models as Descriptors of Neonatal Heart Rate in Mortality Prediction
Explaining Temporal Effects in Sepsis Prediction
Exploring multi-site dataset shifts in electronic health records using time series features
Exploring Time-Step Size in Reinforcement Learning for Sepsis Treatment
Flow-Guided Neural Operator for Self-Supervised Learning on Time Series Data
Foundation Models for Hemodynamic Time Series: A New Paradigm in Cardiovascular Data Modeling
GI-Clust: Deep Clustering for Early Gastrointestinal Cancer Detection
Healthcare TimeSeries Reasoning Benchmarks at Scale
High-Fidelity Synthetic ECG Generation via Mel-Spectrogram Informed Diffusion Training
Improving Forecasts of Suicide Attempts for Patients with Little Data
Integrating Slow Neural Oscillations and Physiological Burden for Trait Anxiety Prediction
Interpretable Graph Learning on Irregular Clinical Time Series
JETS: A Self-Supervised Joint Embedding Time Series Foundation Model for Behavioral Data in Healthcare
Learning Model Parameter Dynamics in a Combination Therapy for Bladder Cancer from Sparse Biological Data
Learning Representations from Incomplete EHR Data with Dual-Masked Autoencoding
Let the Experts Speak: Improving Survival Prediction & Calibration via Mixture-of-Experts Heads
Mapping the Dynamics of Atrial Fibrillation with Spatiotemporal Graph Neural Networks
Multi–Cancer Risk Prediction Using Transformers Trained on Large-Scale Longitudinal EHR Data
Neo-InstructTime: Editing Deceleration Events in Neonatal Vital Signs Using Natural Language
NEUROSKY–EPI: The First Open Single–Electrode Epilepsy EEG Dataset with Context–Aware Modeling and Clinically Grounded Metadata
No Imputation Needed: A Switch Approach to Irregularly Sampled Time Series
Non-invasive electromyographic speech neuroprosthesis: a geometric perspective
PathoFM: Toward a Foundation Model for Pathological Gait
Peak-R1: Instruction-Tuned Large Language Models for Robust J-Peak Detection in Cardiomechanical Signals
Phase-driven Generalizable Representation Learning for Nonstationary Time Series Classification
PPG-Distill: Efficient Photoplethysmography Signals Analysis via Foundation Model Distillation
Predicting Dementia Risk Using Longitudinal Electronic Health Records Data
Predicting Mortality in ICU Patient with Hypertension Using Machine Learning on EHR Data
Pretraining Patient Foundation Models on Multimodal Patient Journeys
Probabilistic Digital Twin for Data-driven Smart Weaning of Mechanical Circulatory Devices
Projection-based Robust Interpretable Signal Mixing for Remote Heart Rate Estimation
Prune or Quantize? Layer-wise Compression of Time-Series ECG Foundation Networks
PULSE-LAB: A Multimodal Hybrid State-Space Model for Forecasting the Presence of Thoracic Pathologies from ECG Time Series and Laboratory Data
RAF: A Model Agnostic Framework for Retrieval Augmented Zero Shot Time Series Forecasting
RAxSS: Retrieval-Augmented Sparse Sampling for Explainable Variable-Length Medical Time Series Classification
Realistic CDSS Drug Dosing with End-to-end Recurrent Q-learning for Dual Vasopressor Control
Riemannian Transfer Learning in Motor Imagery decoding: Reproducibility and Standardized Benchmarks
RoseCDL: Robust and Scalable Convolutional Dictionary Learning for Rare-event Detection
Safe Active Learning of Cerebrospinal Fluid Dynamics
Segment-Then-Connect: Change Point Dynamic Connectivity for Early MCI Detection
Self-DANA: A Resource-Efficient Channel-Adaptive Self-Supervised Approach for Foundation Models
Self-Supervised Learning for Gestational Age Estimation from Low-Cost Doppler Ultrasound in Low-Resource Settings
Signals of Decline: Machine Learning driven Biomarkers for Alzheimer’s Disease
SleepLong: Towards Generating Long-Sequence Sleep Heart Rate Signals with Conditional Diffusion
Speech Foundation Models Generalize to Time Series Tasks from Wearable Sensor Data
SSM-CGM: Interpretable State-Space Forecasting Model of Continuous Glucose Monitoring for Personalized Diabetes Management
Subject-Aware Contrastive Learning for EEG Foundation Models
Task-Aware Functional Hypergraph Learning for Brain State Classification via Information Bottleneck
Temporal Gaze Dynamics as Zero-Shot Prompts for Volumetric Medical Segmentation
TIDAL: A Temporal Causal Diffusion Framework for Visualizing Knee Osteoarthritis Treatment Outcomes
Time-Aware Synthetic Control
Tokenizing Single-Channel EEG with Time-Frequency Motif Learning
Towards Characterizing Knowledge Distillation of PPG Heart Rate Estimation Models
Towards Evaluating Robustness of EEG-based Sleep Trackers
Towards On-device Foundation Models for Raw Wearable Signals
Towards Self-Supervised Foundation Models for Critical Care Time Series
Transferring Clinical Knowledge into ECGs Representation
Transient Neural Dynamics Reconstruction
Translating Deep Learning to Clinical Practice: External Validation and Clinical Benefit of an Electrocardiogram-Based Neural Network for Detecting Low Ejection Fraction
TrendGNN: Towards Understanding of Epidemics, Beliefs, and Behaviors
Two-Stage Modeling for Dynamic Survival Prediction from Longitudinal Data
Uncovering Trajectory and Topological Signatures in Multimodal Pediatric Sleep Embeddings
Using LLMs for Late Multimodal Sensor Fusion for Activity Recognition
Video CLIP Model for Multi-View Echocardiography Interpretation
Volatility-Aware Masking Improves Performance and Efficiency of Pretrained EHR Foundation Models
Wavelet-Based Masked Multiscale Reconstruction for PPG Foundation Models