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Laplace Redux -- Effortless Bayesian Deep Learning

Laplace Redux -- Effortless Bayesian Deep Learning

28 June 2021
Erik A. Daxberger
Agustinus Kristiadi
Alexander Immer
Runa Eschenhagen
Matthias Bauer
Philipp Hennig
    BDL
    UQCV
ArXivPDFHTML

Papers citing "Laplace Redux -- Effortless Bayesian Deep Learning"

11 / 211 papers shown
Title
Active Learning in Bayesian Neural Networks with Balanced Entropy
  Learning Principle
Active Learning in Bayesian Neural Networks with Balanced Entropy Learning Principle
J. Woo
15
11
0
30 May 2021
deepregression: a Flexible Neural Network Framework for Semi-Structured
  Deep Distributional Regression
deepregression: a Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression
David Rügamer
Chris Kolb
Cornelius Fritz
Florian Pfisterer
Philipp Kopper
...
Dominik Thalmeier
Philipp F. M. Baumann
Lucas Kook
Nadja Klein
Christian L. Müller
BDL
8
19
0
06 Apr 2021
All You Need is a Good Functional Prior for Bayesian Deep Learning
All You Need is a Good Functional Prior for Bayesian Deep Learning
Ba-Hien Tran
Simone Rossi
Dimitrios Milios
Maurizio Filippone
OOD
BDL
12
56
0
25 Nov 2020
Bayesian Deep Learning via Subnetwork Inference
Bayesian Deep Learning via Subnetwork Inference
Erik A. Daxberger
Eric T. Nalisnick
J. Allingham
Javier Antorán
José Miguel Hernández-Lobato
UQCV
BDL
12
83
0
28 Oct 2020
BayesAdapter: Being Bayesian, Inexpensively and Reliably, via Bayesian
  Fine-tuning
BayesAdapter: Being Bayesian, Inexpensively and Reliably, via Bayesian Fine-tuning
Zhijie Deng
Jun Zhu
BDL
21
9
0
05 Oct 2020
Probabilistic Spatial Transformer Networks
Probabilistic Spatial Transformer Networks
Pola Schwobel
Frederik Warburg
Martin Jørgensen
Kristoffer Hougaard Madsen
Søren Hauberg
18
8
0
07 Apr 2020
Fast Predictive Uncertainty for Classification with Bayesian Deep
  Networks
Fast Predictive Uncertainty for Classification with Bayesian Deep Networks
Marius Hobbhahn
Agustinus Kristiadi
Philipp Hennig
BDL
UQCV
69
30
0
02 Mar 2020
Semi-Structured Distributional Regression -- Extending Structured
  Additive Models by Arbitrary Deep Neural Networks and Data Modalities
Semi-Structured Distributional Regression -- Extending Structured Additive Models by Arbitrary Deep Neural Networks and Data Modalities
David Rügamer
Chris Kolb
Nadja Klein
8
22
0
13 Feb 2020
Megatron-LM: Training Multi-Billion Parameter Language Models Using
  Model Parallelism
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism
M. Shoeybi
M. Patwary
Raul Puri
P. LeGresley
Jared Casper
Bryan Catanzaro
MoE
243
1,791
0
17 Sep 2019
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
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