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Neural Expectation Maximization

Neural Expectation Maximization

11 August 2017
Klaus Greff
Sjoerd van Steenkiste
Jürgen Schmidhuber
    OCL
ArXivPDFHTML

Papers citing "Neural Expectation Maximization"

16 / 16 papers shown
Title
FACTS: A Factored State-Space Framework For World Modelling
FACTS: A Factored State-Space Framework For World Modelling
Li Nanbo
Firas Laakom
Yucheng Xu
Wenyi Wang
Jürgen Schmidhuber
AI4TS
411
0
0
28 Oct 2024
Exploring the Effectiveness of Object-Centric Representations in Visual Question Answering: Comparative Insights with Foundation Models
Exploring the Effectiveness of Object-Centric Representations in Visual Question Answering: Comparative Insights with Foundation Models
Amir Mohammad Karimi Mamaghan
Samuele Papa
Karl Henrik Johansson
Stefan Bauer
Andrea Dittadi
OCL
82
7
0
22 Jul 2024
Unsupervised Discovery of Object-Centric Neural Fields
Unsupervised Discovery of Object-Centric Neural Fields
Rundong Luo
Hong-Xing Yu
Jiajun Wu
3DPC
OCL
128
4
0
12 Feb 2024
Explicitly Disentangled Representations in Object-Centric Learning
Explicitly Disentangled Representations in Object-Centric Learning
Riccardo Majellaro
Jonathan Collu
Aske Plaat
Thomas M. Moerland
CoGe
OOD
OCL
102
1
0
18 Jan 2024
Recurrent Ladder Networks
Recurrent Ladder Networks
Isabeau Prémont-Schwarz
Alexander Ilin
T. Hao
Antti Rasmus
Rinu Boney
Harri Valpola
52
41
0
28 Jul 2017
SfM-Net: Learning of Structure and Motion from Video
SfM-Net: Learning of Structure and Motion from Video
Sudheendra Vijayanarasimhan
Susanna Ricco
Cordelia Schmid
Rahul Sukthankar
Katerina Fragkiadaki
MDE
63
440
0
25 Apr 2017
Learning Features by Watching Objects Move
Learning Features by Watching Objects Move
Deepak Pathak
Ross B. Girshick
Piotr Dollár
Trevor Darrell
Bharath Hariharan
SSL
VOS
OCL
60
523
0
19 Dec 2016
Tagger: Deep Unsupervised Perceptual Grouping
Tagger: Deep Unsupervised Perceptual Grouping
Klaus Greff
Antti Rasmus
Mathias Berglund
T. Hao
Jürgen Schmidhuber
Harri Valpola
OCL
48
161
0
21 Jun 2016
InfoGAN: Interpretable Representation Learning by Information Maximizing
  Generative Adversarial Nets
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
Xi Chen
Yan Duan
Rein Houthooft
John Schulman
Ilya Sutskever
Pieter Abbeel
GAN
140
4,224
0
12 Jun 2016
Learning visual groups from co-occurrences in space and time
Learning visual groups from co-occurrences in space and time
Phillip Isola
Daniel Zoran
Dilip Krishnan
Edward H. Adelson
48
122
0
21 Nov 2015
Binding via Reconstruction Clustering
Binding via Reconstruction Clustering
Klaus Greff
R. Srivastava
Jürgen Schmidhuber
OCL
38
40
0
19 Nov 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
850
149,474
0
22 Dec 2014
Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures
Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures
J. Hershey
Jonathan Le Roux
F. Weninger
BDL
82
430
0
09 Sep 2014
Neuronal Synchrony in Complex-Valued Deep Networks
Neuronal Synchrony in Complex-Valued Deep Networks
David P. Reichert
Thomas Serre
48
110
0
20 Dec 2013
Deep Learning of Representations: Looking Forward
Deep Learning of Representations: Looking Forward
Yoshua Bengio
150
679
0
02 May 2013
Learning efficient sparse and low rank models
Learning efficient sparse and low rank models
Pablo Sprechmann
A. Bronstein
Guillermo Sapiro
148
192
0
14 Dec 2012
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