AECSF: Adaptive Ensemble Conditional Score Filtering for High-Dimensional Nonlinear Data Assimilation

arXiv:2609.32411 · stat.ML, cs.LG, cs.NA, math.NA · Submitted 2026-09-26 · Read on arXiv

stat.ML, cs.LG, cs.NA, math.NA

Submitted: 2026-09-26

Updated: 2026-10-02

Terminology

• Data Assimilation — 16× in this paper · explained in 2 episodes
• Accuracy — 12× in this paper · explained in 1 episode
• Benchmark — 10× in this paper · explained in 2 episodes
• Adaptation — 8× in this paper · explained in 1 episode
• Consistency — 7× in this paper · explained in 3 episodes
• Diffusion Model — 5× in this paper · explained in 8 episodes
• Inverse Problem — 5× in this paper · explained in 2 episodes
• Diffusion Models — 4× in this paper · explained in 6 episodes
• Uncertainty Quantification — 4× in this paper · explained in 8 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Aggregation — 3× in this paper · explained in 1 episode
• Adaptive Ensemble Conditional Score Filter — 2× in this paper
• Generative Modeling — 2× in this paper · explained in 3 episodes
• Intrinsic Dimension — 2× in this paper · explained in 2 episodes
• Adaptive Sampling — 1× in this paper · explained in 1 episode
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Computational Tractability — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Curse of Dimensionality — 1× in this paper · explained in 6 episodes
• Degeneracy — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Latent Dynamics — 1× in this paper · explained in 2 episodes
• Probabilistic Forecasting — 1× in this paper · explained in 3 episodes
• Score Function — 1× in this paper · explained in 4 episodes
• Selection Bias — 1× in this paper · explained in 4 episodes

Sources

• Closed-form conditional diffusion models for data assimilation
• Multilevel and Sequential Monte Carlo for Training-Free Diffusion Guidance
• Exact Conditional Score-Guided Generative Modeling for Amortized Inference in Uncertainty Quantification

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