Distributional Balancing with Machine Learning for Clinical Trial Augmentation Using Real-World Data

arXiv:2609.23524 · stat.ME, stat.ML · Submitted 2026-09-20 · Read on arXiv

stat.ME, stat.ML

Submitted: 2026-09-20

Updated: 2026-09-20

Code: https://github.com/Zernjk/DBML

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

Terminology

• Causal Inference — 7× in this paper · explained in 4 episodes
• Generative Model — 7× in this paper · explained in 2 episodes
• Local Pivotal Method — 5× in this paper
• Latent Representation — 4× in this paper · explained in 2 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Generative Models — 3× in this paper · explained in 2 episodes
• Latent Representations — 3× in this paper · explained in 3 episodes
• Reconstruction Error — 3× in this paper · explained in 2 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Sparsity — 2× in this paper · explained in 4 episodes
• Super-Learner Index — 2× in this paper
• Accuracy — 1× in this paper · explained in 1 episode
• Bayesian Framework — 1× in this paper · explained in 3 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Core — 1× in this paper · explained in 2 episodes
• Distribution Matching — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Hilbert Space — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Placental Abruption and Cardiovascular Event Risk — 1× in this paper
• Regret — 1× in this paper · explained in 3 episodes
• Reproducing Kernel Hilbert Space (RKHS) — 1× in this paper · explained in 3 episodes
• Synthetic Data Generation — 1× in this paper · explained in 5 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes
• Uniform Manifold Approximation and Projection — 1× in this paper
• Variational Autoencoder (VAE) — 1× in this paper · explained in 3 episodes
• Variational Bayes — 1× in this paper · explained in 2 episodes

Sources

• Advancing Evidence Generation in Biomedical Research Using Natural Hermite and Propensity Score Indices: Applications to External Control Arms
• Deep Learning for Anomaly Detection: A Survey
• Distributional Balancing for Causal Inference: A Unified Framework via Characteristic Function Distance
• Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection

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