Generative Nested Sampling of Atomistic Thermodynamic Landscapes

arXiv:2609.03193 · cond-mat.stat-mech, cs.LG, physics.comp-ph · Submitted 2026-09-02 · Read on arXiv

cond-mat.stat-mech, cs.LG, physics.comp-ph

Submitted: 2026-09-02

Updated: 2026-09-02

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

Terminology

• Nested Sampling — 48× in this paper
• Normalizing Flow — 36× in this paper · explained in 3 episodes
• Normalizing Flows — 22× in this paper · explained in 4 episodes
• Generative Model — 18× in this paper · explained in 2 episodes
• Generative Models — 9× in this paper · explained in 2 episodes
• Benchmark — 6× in this paper · explained in 2 episodes
• Bayesian Inference — 4× in this paper · explained in 5 episodes
• Degeneracy — 4× in this paper · explained in 3 episodes
• Non-Gaussianity — 4× in this paper · explained in 2 episodes
• Fisher Information — 3× in this paper · explained in 3 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Mode Collapse — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Active Learning — 1× in this paper · explained in 6 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Anisotropy — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Core — 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
• Fidelity — 1× in this paper · explained in 2 episodes
• Flow Matching — 1× in this paper · explained in 7 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• One Cycle and Cosine Annealing — 1× in this paper

Sources

• Improving Gradient-guided Nested Sampling for Posterior Inference
• Variational Inference with Normalizing Flows
• Targeted free energy estimation via learned mappings
• Adaptive Monte Carlo augmented with normalizing flows
• Neural Spline Flows
• Annealing in variational inference mitigates mode collapse: A theoretical study on Gaussian mixtures
• Annealing Flow Generative Models Towards Sampling High-Dimensional and Multi-Modal Distributions
• FlowVAT: Normalizing Flow Variational Inference with Affine-Invariant Tempering

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