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. 2402.01960
  4. Cited By
Calibrated Uncertainty Quantification for Operator Learning via
  Conformal Prediction

Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction

2 February 2024
Ziqi Ma
Kamyar Azizzadenesheli
A. Anandkumar
ArXivPDFHTML

Papers citing "Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction"

4 / 4 papers shown
Title
Valid Error Bars for Neural Weather Models using Conformal Prediction
Valid Error Bars for Neural Weather Models using Conformal Prediction
Vignesh Gopakumar
Joel Oskarrson
Ander Gray
L. Zanisi
Stanislas Pamela
Daniel Giles
Matt Kusner
M. Deisenroth
30
0
0
20 Jun 2024
Distribution-Free, Risk-Controlling Prediction Sets
Distribution-Free, Risk-Controlling Prediction Sets
Stephen Bates
Anastasios Nikolas Angelopoulos
Lihua Lei
Jitendra Malik
Michael I. Jordan
OOD
187
186
0
07 Jan 2021
Fourier Neural Operator for Parametric Partial Differential Equations
Fourier Neural Operator for Parametric Partial Differential Equations
Zong-Yi Li
Nikola B. Kovachki
Kamyar Azizzadenesheli
Burigede Liu
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
AI4CE
238
2,298
0
18 Oct 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,145
0
06 Jun 2015
1