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. 1704.01382
  4. Cited By
On the construction of probabilistic Newton-type algorithms

On the construction of probabilistic Newton-type algorithms

5 April 2017
A. Wills
Thomas B. Schon
ArXivPDFHTML

Papers citing "On the construction of probabilistic Newton-type algorithms"

4 / 4 papers shown
Title
Hierarchical Inducing Point Gaussian Process for Inter-domain
  Observations
Hierarchical Inducing Point Gaussian Process for Inter-domain Observations
Luhuan Wu
Andrew C. Miller
Lauren Anderson
Geoff Pleiss
David M. Blei
John P. Cunningham
27
8
0
28 Feb 2021
Empirical study towards understanding line search approximations for
  training neural networks
Empirical study towards understanding line search approximations for training neural networks
Younghwan Chae
D. Wilke
27
11
0
15 Sep 2019
Stochastic quasi-Newton with line-search regularization
Stochastic quasi-Newton with line-search regularization
A. Wills
Thomas B. Schon
ODL
29
21
0
03 Sep 2019
Learning nonlinear state-space models using smooth particle-filter-based
  likelihood approximations
Learning nonlinear state-space models using smooth particle-filter-based likelihood approximations
Andreas Svensson
Fredrik Lindsten
Thomas B. Schon
11
6
0
29 Nov 2017
1