ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1903.08507
  4. Cited By
Safe and adaptive importance sampling: a mixture approach

Safe and adaptive importance sampling: a mixture approach

20 March 2019
B. Delyon
Franccois Portier
ArXivPDFHTML

Papers citing "Safe and adaptive importance sampling: a mixture approach"

3 / 3 papers shown
Title
Adaptive Importance Sampling meets Mirror Descent: a Bias-variance
  tradeoff
Adaptive Importance Sampling meets Mirror Descent: a Bias-variance tradeoff
Anna Korba
Franccois Portier
35
12
0
29 Oct 2021
Infinite-dimensional gradient-based descent for alpha-divergence
  minimisation
Infinite-dimensional gradient-based descent for alpha-divergence minimisation
Kamélia Daudel
Randal Douc
Franccois Portier
23
17
0
20 May 2020
Collective Proposal Distributions for Nonlinear MCMC samplers:
  Mean-Field Theory and Fast Implementation
Collective Proposal Distributions for Nonlinear MCMC samplers: Mean-Field Theory and Fast Implementation
Grégoire Clarté
A. Diez
Jean Feydy
16
7
0
18 Sep 2019
1