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. 2108.12657
  4. Cited By
Variational Inference with NoFAS: Normalizing Flow with Adaptive
  Surrogate for Computationally Expensive Models

Variational Inference with NoFAS: Normalizing Flow with Adaptive Surrogate for Computationally Expensive Models

28 August 2021
Yu Wang
F. Liu
Daniele E. Schiavazzi
    TPM
    BDL
ArXivPDFHTML

Papers citing "Variational Inference with NoFAS: Normalizing Flow with Adaptive Surrogate for Computationally Expensive Models"

7 / 7 papers shown
Title
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling
Alex Glyn-Davies
Arnaud Vadeboncoeur
O. Deniz Akyildiz
Ieva Kazlauskaite
Mark Girolami
PINN
70
0
0
10 Sep 2024
InVAErt networks: a data-driven framework for model synthesis and
  identifiability analysis
InVAErt networks: a data-driven framework for model synthesis and identifiability analysis
Guoxiang Grayson Tong
Carlos A. Sing Long
Daniele E. Schiavazzi
28
7
0
24 Jul 2023
LINFA: a Python library for variational inference with normalizing flow
  and annealing
LINFA: a Python library for variational inference with normalizing flow and annealing
Yu Wang
Emma R. Cobian
Jubilee Lee
Fang Liu
J. Hauenstein
Daniele E. Schiavazzi
BDL
AI4CE
26
0
0
10 Jul 2023
Tensorizing flows: a tool for variational inference
Tensorizing flows: a tool for variational inference
Y. Khoo
M. Lindsey
Renana Keydar
DRL
20
4
0
03 May 2023
AdaAnn: Adaptive Annealing Scheduler for Probability Density
  Approximation
AdaAnn: Adaptive Annealing Scheduler for Probability Density Approximation
Emma R. Cobian
J. Hauenstein
Fang Liu
Daniele E. Schiavazzi
19
4
0
01 Feb 2022
A Probabilistic Graphical Model Foundation for Enabling Predictive
  Digital Twins at Scale
A Probabilistic Graphical Model Foundation for Enabling Predictive Digital Twins at Scale
Michael G. Kapteyn
Jacob V. R. Pretorius
Karen E. Willcox
34
214
0
10 Dec 2020
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
185
3,266
0
09 Jun 2012
1