Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

212
Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...
212

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Streamlined optical training of large-scale modern deep learning architectures with direct feedback alignment.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Inference in spreading processes with neural-network priors.

Physical review. E·2026
Same author

Dynamical cavity method for hypergraphs and its application to quenches in the k-XOR-SAT problem.

Physical review. E·2025
Same author

Integer traffic assignment problem: Algorithms and insights on random graphs.

Physical review. E·2025
Same author

Dynamical phase transitions in graph cellular automata.

Physical review. E·2024
Same author

Gaussian universality of perceptrons with random labels.

Physical review. E·2024

相关实验视频

Updated: Jun 23, 2025

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

8.5K

从旋转玻璃的角度对流量,扩散和自回归神经网络进行采样.

Davide Ghio1, Yatin Dandi1,2, Florent Krzakala1

  • 1Information, Learning and Physics Laboratory, École Polytechnique Fédérale de Lausanne, Lausanne CH-1015, Switzerland.

Proceedings of the National Academy of Sciences of the United States of America
|June 24, 2024
PubMed
概括

像流和扩散网络这样的生成模型由于相位过渡而难以获得采样效率. 传统的方法,如蒙特卡洛和朗格温动力学,有时会超过这些先进的技术.

关键词:
自动回归网络是自动回归网络.扩散生成的模型是扩散生成的模型.基于流量的模型.采样采样 采样采样旋转眼镜的眼镜是什么意思

更多相关视频

Probing Structural and Dynamic Properties of Trafficking Subcellular Nanostructures by Spatiotemporal Fluctuation Spectroscopy
08:17

Probing Structural and Dynamic Properties of Trafficking Subcellular Nanostructures by Spatiotemporal Fluctuation Spectroscopy

Published on: August 16, 2021

1.9K
Spatial Temporal Analysis of Fieldwise Flow in Microvasculature
09:39

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

Published on: November 18, 2019

5.8K

相关实验视频

Last Updated: Jun 23, 2025

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

8.5K
Probing Structural and Dynamic Properties of Trafficking Subcellular Nanostructures by Spatiotemporal Fluctuation Spectroscopy
08:17

Probing Structural and Dynamic Properties of Trafficking Subcellular Nanostructures by Spatiotemporal Fluctuation Spectroscopy

Published on: August 16, 2021

1.9K
Spatial Temporal Analysis of Fieldwise Flow in Microvasculature
09:39

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

Published on: November 18, 2019

5.8K

科学领域:

  • 机器学习 机器学习
  • 统计物理 统计物理
  • 计算科学 计算科学

背景情况:

  • 强大的生成模型 (流量,扩散,自动回归网络) 在数据生成方面表现出色.
  • 对它们的性能和局限性的理论分析仍然是一个挑战.

研究的目的:

  • 对已知分布的问题分析生成模型的采样效率.
  • 将他们的表现与传统方法 (蒙特卡洛马尔科夫链,朗格文动态) 进行比较.

主要方法:

  • 专注于来自无序系统的概率分布 (旋转眼镜,推理,约束满足).
  • 将生成采样映射到一个修改的概率测量的贝叶斯最佳表示.
  • 分析特定问题类的采样性能.

主要成果:

  • 生成模型面临的采样困难是由于第一阶段的阶段过渡在denoising路径.
  • 确定了生成模型失败但传统方法成功的参数区域.
  • 确定了传统方法失败但生成模型成功的参数区域.

结论:

  • 在某些条件下,生成模型在采样效率方面存在局限性.
  • 传统的采样方法在特定场景中具有优势.
  • 混合方法或根据问题的特征仔细选择方法是有必要的.