Multimodal Empirical Bayes Variational Autoencoders for Joint Longitudinal and Time-to-Event Modeling

arXiv:2607.13984 · stat.ML, cs.LG · Submitted 2026-07-15 · Read on arXiv

Anders Sjöberg, Nils Olsson, Marcus Baaz, Mats Jirstrand

stat.ML, cs.LG

Submitted: 2026-07-15

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Decoder — 52× in this paper · explained in 2 episodes
• Stability Selection — 7× in this paper · explained in 2 episodes
• Latent Variables — 6× in this paper · explained in 2 episodes
• Generalization — 5× in this paper · explained in 14 episodes
• Latent Representation — 5× in this paper · explained in 2 episodes
• COSMIC Cancer Gene Census — 3× in this paper
• Training Objective — 3× in this paper · explained in 3 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 3 episodes
• Feature Extraction — 2× in this paper · explained in 3 episodes
• Hybrid Model — 2× in this paper · explained in 2 episodes
• Overfitting — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 6 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Embeddings — 1× in this paper · explained in 2 episodes
• Hierarchical Structure — 1× in this paper · explained in 3 episodes
• Hybrid Approaches — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Kullback–Leibler Divergence — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Longitudinal Data — 1× in this paper · explained in 2 episodes
• Modular Approach — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Sparsity — 1× in this paper · explained in 5 episodes
• Two-stage training — 1× in this paper · explained in 2 episodes
• Variational Bayes — 1× in this paper · explained in 2 episodes
• Weight Decay — 1× in this paper · explained in 2 episodes

Sources

• Variational autoencoder for inference of nonlinear mixed effect models based on ordinary differential equations
• Auto-Encoding Variational Bayes

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