Lagrangian--Hamiltonian Flows for Video Prediction and Image Generation: A Symplectic Perspective

arXiv:2609.35710 · cs.CV · Submitted 2026-09-28 · Read on arXiv

cs.CV

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/Lilas-Q/Geometric_quantization_models

Terminology

Flow Matching — 21× in this paper · explained in 8 episodes
Accuracy — 7× in this paper · explained in 1 episode
Transformer — 3× in this paper · explained in 2 episodes
Adam — 2× in this paper · explained in 2 episodes
Generative Model — 2× in this paper · explained in 2 episodes
Generative Modeling — 2× in this paper · explained in 3 episodes
Generative Models — 2× in this paper · explained in 3 episodes
Normalizing Flow — 2× in this paper · explained in 3 episodes
Normalizing Flows — 2× in this paper · explained in 4 episodes
Optimal Transport — 2× in this paper · explained in 5 episodes
Quantization — 2× in this paper · explained in 12 episodes
Benchmark — 1× in this paper · explained in 2 episodes
Data Augmentation — 1× in this paper · explained in 7 episodes
Diffusion Model — 1× in this paper · explained in 8 episodes
Diffusion Models — 1× in this paper · explained in 6 episodes
Distillation — 1× in this paper · explained in 2 episodes
Exponential Moving Average (EMA) — 1× in this paper · explained in 2 episodes
Fidelity — 1× in this paper · explained in 2 episodes
Fine-Tuning — 1× in this paper · explained in 5 episodes
Generative AI — 1× in this paper · explained in 2 episodes
Latent Dynamics — 1× in this paper · explained in 2 episodes
Linear probe — 1× in this paper · explained in 2 episodes
Non-stationarity — 1× in this paper · explained in 2 episodes

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