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Uncertainty modeling for fine-tuned implicit functions

Uncertainty modeling for fine-tuned implicit functions

17 June 2024
A. Susmelj
Mael Macuglia
Nataša Tagasovska
Reto Sutter
Sebastiano Caprara
Jean-Philippe Thiran
E. Konukoglu
ArXivPDFHTML

Papers citing "Uncertainty modeling for fine-tuned implicit functions"

5 / 5 papers shown
Title
Dense Depth Priors for Neural Radiance Fields from Sparse Input Views
Dense Depth Priors for Neural Radiance Fields from Sparse Input Views
Barbara Roessle
Jonathan T. Barron
B. Mildenhall
Pratul P. Srinivasan
Matthias Nießner
VGen
114
352
0
06 Dec 2021
Convolutional Occupancy Networks
Convolutional Occupancy Networks
Songyou Peng
Michael Niemeyer
L. Mescheder
Marc Pollefeys
Andreas Geiger
3DV
AI4CE
209
860
0
10 Mar 2020
Deep Reinforcement Learning for Autonomous Driving: A Survey
Deep Reinforcement Learning for Autonomous Driving: A Survey
B. R. Kiran
Ibrahim Sobh
V. Talpaert
Patrick Mannion
A. A. Sallab
S. Yogamani
P. Pérez
137
1,599
0
02 Feb 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,635
0
05 Dec 2016
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
9,042
0
06 Jun 2015
1