Generalized Engression Models

arXiv:2610.01823 · stat.ME, cs.LG, stat.ML · Submitted 2026-10-01 · Read on arXiv

stat.ME, cs.LG, stat.ML

Submitted: 2026-10-01

Updated: 2026-10-01

Code: https://github.com/xwshen51/engression

Terminology

• Benchmark — 35× in this paper · explained in 2 episodes
• AUC — 29× in this paper · explained in 2 episodes
• Copula — 24× in this paper · explained in 2 episodes
• Generative Model — 15× in this paper · explained in 2 episodes
• Generative Models — 10× in this paper · explained in 2 episodes
• Accuracy — 9× in this paper · explained in 1 episode
• Calibration — 9× in this paper · explained in 7 episodes
• Adam — 5× in this paper · explained in 2 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Diffusion Model — 3× in this paper · explained in 8 episodes
• Diffusion Models — 3× in this paper · explained in 6 episodes
• Core — 2× in this paper · explained in 2 episodes
• Normalizing Flow — 2× in this paper · explained in 3 episodes
• Normalizing Flows — 2× in this paper · explained in 4 episodes
• Probabilistic Forecasting — 2× in this paper · explained in 3 episodes
• Abundance — 1× in this paper · explained in 1 episode
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Neural Network Approximation — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes
• Variational Bayes — 1× in this paper · explained in 2 episodes

Sources

• Error Analysis of Neural-Network-Based Engression
• Theoretical Analysis of Engression and Reverse Markov Engression

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