A data-driven Fourier-mixture neural-network method for density estimation

arXiv:2605.18019 · stat.ML, q-fin.CP · Submitted 2026-05-18 · Read on arXiv

stat.ML, q-fin.CP

Submitted: 2026-05-18

Updated: 2026-09-11

Comments: 27 pages, 5 figures

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

Terminology

• Benchmark — 17× in this paper · explained in 2 episodes
• Adam — 4× in this paper · explained in 2 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Calibration — 3× in this paper · explained in 7 episodes
• Diffusion Model — 3× in this paper · explained in 8 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Diffusion Process — 1× in this paper · explained in 2 episodes
• Error Decomposition — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Neural Network Approximation — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Two-Stage Optimization — 1× in this paper · explained in 2 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes

Sources

• Monotone 2D Integration Scheme for Mean-CVaR Optimization via Fourier-Trained Transition Kernels
• Adam: A Method for Stochastic Optimization

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