Copertina

A Minimum Variance Path Principle for Accurate and Stable Score-Based Density Ratio Estimation

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Chen, Wei, Li, Jiacheng, Li, Shigui, Lin, Zhiqi, Yang, Junmei, Paisley, John, Zeng, Delu
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Diffusion Secant Alignment for Score-Based Density Ratio Estimation
di: Chen, Wei, et al.
Pubblicazione: (2025)

Dequantified Diffusion-Schr{ö}dinger Bridge for Density Ratio Estimation
di: Chen, Wei, et al.
Pubblicazione: (2025)

One-Step Score-Based Density Ratio Estimation
di: Chen, Wei, et al.
Pubblicazione: (2026)

Flexible Bayesian Last Layer Models Using Implicit Priors and Diffusion Posterior Sampling
di: Xu, Jian, et al.
Pubblicazione: (2024)

Fully Bayesian Differential Gaussian Processes through Stochastic Differential Equations
di: Xu, Jian, et al.
Pubblicazione: (2024)

Consist-Retinex: One-Step Noise-Emphasized Consistency Training Accelerates High-Quality Retinex Enhancement
di: Xu, Jian, et al.
Pubblicazione: (2025)

EVODiff: Entropy-aware Variance Optimized Diffusion Inference
di: Li, Shigui, et al.
Pubblicazione: (2025)

Entropy-Informed Weighting Channel Normalizing Flow for Deep Generative Models
di: Chen, Wei, et al.
Pubblicazione: (2024)

Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling
di: Xu, Jian, et al.
Pubblicazione: (2024)

Sparse Variational Student-t Processes for Heavy-tailed Modeling
di: Xu, Jian, et al.
Pubblicazione: (2024)

Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference
di: Xu, Jian, et al.
Pubblicazione: (2024)

Towards Disentangled Preference Optimization Dynamics: Suppress the Loser, Preserve the Winner
di: Chen, Wei, et al.
Pubblicazione: (2026)

Neural Bridge Processes
di: Xu, Jian, et al.
Pubblicazione: (2025)

Bayesian Gaussian Process ODEs via Double Normalizing Flows
di: Xu, Jian, et al.
Pubblicazione: (2023)

Stochastic Schrödinger Diffusion Models for Pure-State Ensemble Generation
di: Xu, Jian, et al.
Pubblicazione: (2026)

Gaussian Process Tilted Nonparametric Density Estimation using Fisher Divergence Score Matching
di: Paisley, John, et al.
Pubblicazione: (2025)

Diffusion Bridge Variational Inference for Deep Gaussian Processes
di: Xu, Jian, et al.
Pubblicazione: (2025)

Onsager-Machlup Posterior Transport for Deep Gaussian Processes
di: Xu, Jian, et al.
Pubblicazione: (2026)

AQKA: Active Quantum Kernel Acquisition Under a Shot Budget
di: Xu, Jian, et al.
Pubblicazione: (2026)

Sparse Variational Student-t Processes
di: Xu, Jian, et al.
Pubblicazione: (2023)

Anomaly Detection with Variance Stabilized Density Estimation
di: Rozner, Amit, et al.
Pubblicazione: (2023)

An Explainable Gaussian Process Auto-encoder for Tabular Data
di: Zhang, Wei, et al.
Pubblicazione: (2025)

Gaussian Process Neural Additive Models
di: Zhang, Wei, et al.
Pubblicazione: (2024)

Spectral Anatomy of Quantum Gaussian Process Kernels
di: Xu, Jian, et al.
Pubblicazione: (2026)

Estimating Covariance for Global Minimum Variance Portfolio: A Decision-Focused Learning Approach
di: Kim, Juchan, et al.
Pubblicazione: (2025)

Neural Operator Variational Inference based on Regularized Stein Discrepancy for Deep Gaussian Processes
di: Xu, Jian, et al.
Pubblicazione: (2023)

Quantum Grid Path Planning Using Parallel QAOA Circuits Based on Minimum Energy Principle
di: Liu, Jun
Pubblicazione: (2025)

Reducing Credit Assignment Variance via Counterfactual Reasoning Paths
di: Ding, Fei, et al.
Pubblicazione: (2026)

Ratio-Variance Regularized Policy Optimization for Efficient LLM Fine-tuning
di: Luo, Yu, et al.
Pubblicazione: (2026)

On the Role of Preference Variance in Preference Optimization
di: Guo, Jiacheng, et al.
Pubblicazione: (2025)

Revisiting Zeroth-Order Optimization: Minimum-Variance Two-Point Estimators and Directionally Aligned Perturbations
di: Ma, Shaocong, et al.
Pubblicazione: (2025)

The Structural Origin of Attention Sink: Variance Discrepancy, Super Neurons, and Dimension Disparity
di: Li, Siquan, et al.
Pubblicazione: (2026)

Minimum Variance Unbiased N:M Sparsity for the Neural Gradients
di: Chmiel, Brian, et al.
Pubblicazione: (2022)

Effective Exploration Based on the Structural Information Principles
di: Zeng, Xianghua, et al.
Pubblicazione: (2024)

Provably Accurate Shapley Value Estimation via Leverage Score Sampling
di: Musco, Christopher, et al.
Pubblicazione: (2024)

General Uncertainty Estimation with Delta Variances
di: Schmitt, Simon, et al.
Pubblicazione: (2025)

A Score-Based Density Formula, with Applications in Diffusion Generative Models
di: Li, Gen, et al.
Pubblicazione: (2024)

Relative Density Ratio Optimization for Stable and Statistically Consistent Model Alignment
di: Takahashi, Hiroshi, et al.
Pubblicazione: (2026)

Density Ratio Estimation with Conditional Probability Paths
di: Yu, Hanlin, et al.
Pubblicazione: (2025)

Hierarchical Decision Making Based on Structural Information Principles
di: Zeng, Xianghua, et al.
Pubblicazione: (2024)