arXiv Machine Learning
Jun 5
Environment-Robust Representation Learning with Empirical Bayes
arXiv:2606. 05365v1 Announce Type: cross Abstract: We consider multi-environment prediction problems.
Context-Aware Hierarchical Bayesian Modeling of IVF Laboratory Environmental Conditions
arXiv:2606. 20459v1 Announce Type: new Abstract: IVF pregnancy rates are routinely modeled using patient-level variables, while high-resolution laboratory environmental data remain underutilized.
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arXiv AI
Jun 12
Is It You or Your Environment? A Bayesian Inference Framework for Genomically-Anchored Personalized Physiological Interpretation
arXiv:2606. 13556v1 Announce Type: new Abstract: Personalized health AI systems face a fundamental cold-start problem: machine learning models for physiological interpretation require weeks of individual behavioral data before they can distinguish constitutional variation from environmentally driven deviation.
arXiv AI
Jun 2
Bayesian Inference of Nonlinear Malaria Dynamics in Ghana via an Ensemble Markov Chain Monte Carlo Sampler
arXiv:2606. 00783v1 Announce Type: cross Abstract: Reliable quantification of malaria dynamics in sub-Saharan Africa is hindered by short, noisy, and spatially heterogeneous surveillance records.
arXiv AI
Jun 26
Simulation-based inference for rapid Bayesian parameter estimation in epidemiological models: a comparison with MCMC
arXiv:2606. 27286v1 Announce Type: new Abstract: Mechanistic epidemiological models are widely used to support infectious disease forecasting and public-health decision making.
arXiv Machine Learning
Jul 15
Auditable Context-Aware HFMD Forecasting with Structured LLM Agents
arXiv:2511. 23276v2 Announce Type: replace Abstract: Effective HFMD surveillance requires forecasts capturing both time-series patterns and contextual drivers such as school calendars, weather, and policy or surveillance reports.
arXiv Machine Learning
Jul 7
Bayesian Invariance Modeling of Multi-Environment Data
arXiv:2506. 22675v4 Announce Type: replace-cross Abstract: Invariant prediction [Peters et al.
arXiv AI
Jul 24
Demographically-Informed Heat-Mortality Risk Curves via Risk Graph Neural Networks
arXiv:2607. 21131v1 Announce Type: cross Abstract: Estimating heat-related mortality risk is a core task in environmental epidemiology, typically addressed with Distributed Lag Non-linear Models (DLNMs); interpretable exposure-response surfaces fitted to temperature-mortality time series.
arXiv AI
Jun 8
A robust PPG foundation model using multimodal physiological supervision
arXiv:2606. 07365v1 Announce Type: cross Abstract: Photoplethysmography (PPG), a non-invasive measure of changes in blood volume, is widely used in both wearable devices and clinical settings.
Hugging Face Trending Papers
Jun 14
Bayesian Networks with Latent Time Embedding for Stage-Aware Causal Modeling of Alzheimer's Disease Progression
Alzheimer's disease (AD) progression is often described through the amyloid-tau-neurodegeneration, or AT(N), cascade. However, most longitudinal models represent this cascade either as a fixed sequence of biomarkers or as a black-box forecasting task.
Hugging Face Trending Papers
6d ago
Intervention-Aware Clinical World Model for Post-Op Outcome Forecasting in Cardiology
Many clinical prediction models treat post-intervention outcomes as a one-step mapping from baseline measurements to a future endpoint. However, recovery after a procedure often unfolds as an irregular trajectory: clinical observations, medication changes, repeat interventions, and physiological measurements are recorded asynchronously and can change risk assessment over time.
arXiv Machine Learning
Jun 16
Bayesian Networks with Latent Time Embedding for Stage-Aware Causal Modeling of Alzheimer's Disease Progression
arXiv:2606. 15784v1 Announce Type: new Abstract: Alzheimer's disease (AD) progression is often described through the amyloid-tau-neurodegeneration, or AT(N), cascade.
arXiv Machine Learning
6d ago
Intervention-Aware Clinical World Model for Post-Op Outcome Forecasting in Cardiology
arXiv:2608. 13518v1 Announce Type: new Abstract: Many clinical prediction models treat post-intervention outcomes as a one-step mapping from baseline measurements to a future endpoint.