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Unifying Approaches in Active Learning and Active Sampling via Fisher
  Information and Information-Theoretic Quantities

Unifying Approaches in Active Learning and Active Sampling via Fisher Information and Information-Theoretic Quantities

1 August 2022
Andreas Kirsch
Y. Gal
    FedML
ArXivPDFHTML

Papers citing "Unifying Approaches in Active Learning and Active Sampling via Fisher Information and Information-Theoretic Quantities"

7 / 7 papers shown
Title
POp-GS: Next Best View in 3D-Gaussian Splatting with P-Optimality
POp-GS: Next Best View in 3D-Gaussian Splatting with P-Optimality
Joey Wilson
Marcelino Almeida
Sachit Mahajan
Martin Labrie
Maani Ghaffari
Omid Ghasemalizadeh
Min Sun
Cheng-Hao Kuo
Arnab Sen
3DGS
53
0
0
10 Mar 2025
Beyond Uncertainty: Risk-Aware Active View Acquisition for Safe Robot Navigation and 3D Scene Understanding with FisherRF
Beyond Uncertainty: Risk-Aware Active View Acquisition for Safe Robot Navigation and 3D Scene Understanding with FisherRF
Guangyi Liu
Wen Jiang
Boshu Lei
Vivek Pandey
Kostas Daniilidis
N. Motee
44
8
0
20 Jan 2025
Next Best Sense: Guiding Vision and Touch with FisherRF for 3D Gaussian Splatting
Next Best Sense: Guiding Vision and Touch with FisherRF for 3D Gaussian Splatting
Matthew Strong
Boshu Lei
Aiden Swann
Wen Jiang
Kostas Daniilidis
Monroe Kennedy III
3DGS
40
3
0
07 Oct 2024
PUP 3D-GS: Principled Uncertainty Pruning for 3D Gaussian Splatting
PUP 3D-GS: Principled Uncertainty Pruning for 3D Gaussian Splatting
Alex Hanson
Allen Tu
Vasu Singla
Mayuka Jayawardhana
Matthias Zwicker
Tom Goldstein
3DGS
39
9
0
14 Jun 2024
Active Preference Learning for Ordering Items In- and Out-of-sample
Active Preference Learning for Ordering Items In- and Out-of-sample
Herman Bergström
Emil Carlsson
Devdatt Dubhashi
Fredrik D. Johansson
25
0
0
05 May 2024
FisherRF: Active View Selection and Uncertainty Quantification for
  Radiance Fields using Fisher Information
FisherRF: Active View Selection and Uncertainty Quantification for Radiance Fields using Fisher Information
Wen Jiang
Boshu Lei
Kostas Daniilidis
3DGS
21
31
0
29 Nov 2023
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
247
9,109
0
06 Jun 2015
1