Bidirectional Autoregressive Latent Diffusion for Forward and Inverse Magnetohydrodynamics

arXiv:2606.29620 · stat.ML, cs.LG, nlin.AO, physics.plasm-ph · Submitted 2026-06-28 · Read on arXiv

Alexander Scheinker

stat.ML, cs.LG, nlin.AO, physics.plasm-ph

Submitted: 2026-06-28

Code: https://github.com/pmocz/c

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

Terminology

• Consistency — 12× in this paper · explained in 3 episodes
• Diffusion Model — 11× in this paper · explained in 10 episodes
• Latent Representation — 8× in this paper · explained in 2 episodes
• Latent Space — 8× in this paper · explained in 7 episodes
• Decoder — 6× in this paper · explained in 2 episodes
• Diffusion Models — 5× in this paper · explained in 9 episodes
• Generative Model — 5× in this paper · explained in 2 episodes
• Accuracy — 4× in this paper · explained in 1 episode
• Generative Models — 4× in this paper · explained in 3 episodes
• Latent Representations — 4× in this paper · explained in 3 episodes
• Autoregressive Rollout — 3× in this paper · explained in 3 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Inverse Problem — 3× in this paper · explained in 2 episodes
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Deep Reinforcement Learning — 2× in this paper · explained in 3 episodes
• Generative Modeling — 2× in this paper · explained in 3 episodes
• Latent Diffusion Model — 2× in this paper · explained in 3 episodes
• Normalizing Flow — 2× in this paper · explained in 3 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Bayesian Inference — 1× in this paper · explained in 6 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Diffusion Processes — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 10 episodes
• Flow Matching — 1× in this paper · explained in 17 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Magnetohydrodynamics (MHD) — 1× in this paper · explained in 4 episodes
• Normalizing Flows — 1× in this paper · explained in 4 episodes
• Optimal Transport — 1× in this paper · explained in 5 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Surrogate Model — 1× in this paper · explained in 3 episodes
• Variational Autoencoder (VAE) — 1× in this paper · explained in 6 episodes
• Vision Transformer (ViT) — 1× in this paper · explained in 2 episodes

Sources

• Flow Matching for Generative Modeling
• Consistency Models
• Posterior Mean Matching: Generative Modeling through Online Bayesian Inference
• Improved Robustness of Deep Reinforcement Learning for Control of Time-Varying Systems by Bounded Extremum Seeking
• Planning for Change: Reinforcement Learning Combined with Bounded Extremum Seeking for Robotic Control under Distribution Shift
• Mahalanobis-Guided Latent OOD Detection for Hybrid ES-DRL Control in Time-Varying Systems

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