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Vector Quantized Bayesian Neural Network Inference for Data Streams

Vector Quantized Bayesian Neural Network Inference for Data Streams

12 July 2019
Namuk Park
Taekyu Lee
Songkuk Kim
    MQ
ArXivPDFHTML

Papers citing "Vector Quantized Bayesian Neural Network Inference for Data Streams"

7 / 7 papers shown
Title
How Do Vision Transformers Work?
How Do Vision Transformers Work?
Namuk Park
Songkuk Kim
ViT
32
465
0
14 Feb 2022
Fast Monte-Carlo Approximation of the Attention Mechanism
Fast Monte-Carlo Approximation of the Attention Mechanism
Hyunjun Kim
Jeonggil Ko
17
2
0
30 Jan 2022
Bayesian Model-Agnostic Meta-Learning
Bayesian Model-Agnostic Meta-Learning
Taesup Kim
Jaesik Yoon
Ousmane Amadou Dia
Sungwoong Kim
Yoshua Bengio
Sungjin Ahn
UQCV
BDL
196
498
0
11 Jun 2018
Probabilistic Model-Agnostic Meta-Learning
Probabilistic Model-Agnostic Meta-Learning
Chelsea Finn
Kelvin Xu
Sergey Levine
BDL
165
666
0
07 Jun 2018
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
270
5,660
0
05 Dec 2016
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image
  Segmentation
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Vijay Badrinarayanan
Alex Kendall
R. Cipolla
SSeg
446
15,637
0
02 Nov 2015
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
9,136
0
06 Jun 2015
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