GlucoFM: A Dual-Stream Foundation Model for Continuous Glucose Monitoring
cs.LG
Submitted: 2026-05-29
Updated: 2026-08-25
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Chronos-2: From Univariate to Universal Forecasting
- MantisV2: Closing the Zero-Shot Gap in Time Series Classification with Synthetic Data and Test-Time Strategies
- One Loss to Rule Them All: Marked Time-to-Event for Structured EHR Foundation Models
- HEARTS: Benchmarking LLM Reasoning on Health Time Series
- ZARA: Training-Free Motion Time-Series Reasoning via Evidence-Grounded LLM Agents
- UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
- CGM-JEPA: Learning Consistent Continuous Glucose Monitor Representations via Predictive Self-Supervised Pretraining
- Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
- OSF: On Pre-training and Scaling of Sleep Foundation Models
- Interpolation-Prediction Networks for Irregularly Sampled Time Series
- LSM-2: Learning from Incomplete Wearable Sensor Data
- SleepLM: Natural-Language Intelligence for Human Sleep
- Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning
Related papers
- Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
- AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
- Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
- Convergence issues in Relational Concept Analysis based on AOC-posets
- Beliefs Beyond Posteriors: The Predictive Cost of ELBO Binding
- Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks