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BRUNO: A Deep Recurrent Model for Exchangeable Data
v1v2v3 (latest)

BRUNO: A Deep Recurrent Model for Exchangeable Data

21 February 2018
I. Korshunova
Jonas Degrave
Ferenc Huszár
Y. Gal
Arthur Gretton
J. Dambre
    BDL
ArXiv (abs)PDFHTML

Papers citing "BRUNO: A Deep Recurrent Model for Exchangeable Data"

19 / 19 papers shown
Title
Incoherent Probability Judgments in Large Language Models
Incoherent Probability Judgments in Large Language Models
Jian-Qiao Zhu
Thomas Griffiths
128
7
0
30 Jan 2024
Decision-Making with Auto-Encoding Variational Bayes
Decision-Making with Auto-Encoding Variational Bayes
Romain Lopez
Pierre Boyeau
Nir Yosef
Michael I. Jordan
Jeffrey Regier
BDL
407
10,591
0
17 Feb 2020
Federated Meta-Learning with Fast Convergence and Efficient
  Communication
Federated Meta-Learning with Fast Convergence and Efficient Communication
Fei Chen
Mi Luo
Zhenhua Dong
Zhenguo Li
Xiuqiang He
FedML
81
395
0
22 Feb 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning
  Algorithms
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
Kashif Rasul
Roland Vollgraf
283
8,883
0
25 Aug 2017
Masked Autoregressive Flow for Density Estimation
Masked Autoregressive Flow for Density Estimation
George Papamakarios
Theo Pavlakou
Iain Murray
210
1,354
0
19 May 2017
Deep Sets
Deep Sets
Manzil Zaheer
Satwik Kottur
Siamak Ravanbakhsh
Barnabás Póczós
Ruslan Salakhutdinov
Alex Smola
408
2,464
0
10 Mar 2017
Matching Networks for One Shot Learning
Matching Networks for One Shot Learning
Oriol Vinyals
Charles Blundell
Timothy Lillicrap
Koray Kavukcuoglu
Daan Wierstra
VLM
373
7,323
0
13 Jun 2016
Towards a Neural Statistician
Towards a Neural Statistician
Harrison Edwards
Amos Storkey
BDL
84
427
0
07 Jun 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning
Faster Eigenvector Computation via Shift-and-Invert Preconditioning
Dan Garber
Laurent Dinh
Chi Jin
Jascha Narain Sohl-Dickstein
Samy Bengio
Praneeth Netrapalli
Aaron Sidford
266
3,702
0
26 May 2016
Weight Normalization: A Simple Reparameterization to Accelerate Training
  of Deep Neural Networks
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks
Tim Salimans
Diederik P. Kingma
ODL
194
1,942
0
25 Feb 2016
Fast and Accurate Deep Network Learning by Exponential Linear Units
  (ELUs)
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)
Djork-Arné Clevert
Thomas Unterthiner
Sepp Hochreiter
300
5,524
0
23 Nov 2015
Order Matters: Sequence to sequence for sets
Order Matters: Sequence to sequence for sets
Oriol Vinyals
Samy Bengio
M. Kudlur
BDL
196
951
0
19 Nov 2015
A note on the evaluation of generative models
A note on the evaluation of generative models
Lucas Theis
Aaron van den Oord
Matthias Bethge
EGVM
126
1,145
0
05 Nov 2015
Variational Inference with Normalizing Flows
Variational Inference with Normalizing Flows
Danilo Jimenez Rezende
S. Mohamed
DRLBDL
313
4,182
0
21 May 2015
Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
463
43,305
0
11 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.8K
150,115
0
22 Dec 2014
Learning Theory for Distribution Regression
Learning Theory for Distribution Regression
Z. Szabó
Bharath K. Sriperumbudur
Barnabás Póczós
Arthur Gretton
OOD
61
138
0
08 Nov 2014
NICE: Non-linear Independent Components Estimation
NICE: Non-linear Independent Components Estimation
Laurent Dinh
David M. Krueger
Yoshua Bengio
DRLBDL
126
2,261
0
30 Oct 2014
Student-t Processes as Alternatives to Gaussian Processes
Student-t Processes as Alternatives to Gaussian Processes
Amar Shah
A. Wilson
Zoubin Ghahramani
GP
90
203
0
18 Feb 2014
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