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Learning modular object-centric representations is crucial for systematic generalization.
Orientation and form
Irvin Rock · 1973
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Some demonstrations of the effects of structural descriptions in mental imagery
Geoffrey Hinton · 1979
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Nonlinear independent component analysis: Existence and uniqueness results
Aapo Hyvärinen and Petteri Pajunen · 1999
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The algebraic mind: Integrating connectionism and cognitive science
Gary F Marcus · 2003
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A theory of causal learning in children: causal maps and bayes nets
Alison Gopnik, Clark Glymour, David M Sobel, Laura E Schulz, Tamar Kushnir, and David Danks · 2004
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How to grow a mind: Statistics, structure, and abstraction
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Representation learning: A review and new perspectives
Yoshua Bengio, Aaron Courville, and Pascal Vincent · 2013
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Deep convolutional inverse graphics network
Tejas D Kulkarni, William F Whitney, Pushmeet Kohli, and Josh Tenenbaum · 2015
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Deep unsupervised clustering with gaussian mixture variational autoencoders
Nat Dilokthanakul, Pedro AM Mediano, Marta Garnelo, Matthew CH Lee, Hugh Salimbeni, Kai Arulkumaran, and Murray Shanahan · 2016
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Elbo surgery: yet another way to carve up the variational evidence lower bound
Matthew D Hoffman and Matthew J Johnson · 2016
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Unsupervised feature extraction by time-contrastive learning and nonlinear ica
Aapo Hyvarinen and Hiroshi Morioka · 2016
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The cognitive map in humans: spatial navigation and beyond
Russell A Epstein, Eva Zita Patai, Joshua B Julian, and Hugo J Spiers · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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beta-VAE: Learning basic visual concepts with a constrained variational framework
Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner · 2017
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Clevr: A diagnostic dataset for compositional language and elementary visual reasoning
Justin Johnson, Bharath Hariharan, Laurens Van Der Maaten, Li Fei-Fei, C Lawrence Zitnick, and Ross Girshick · 2017
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Building machines that learn and think like people
Brenden M Lake, Tomer D Ullman, Joshua B Tenenbaum, and Samuel J Gershman · 2017
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Neural discrete representation learning
Aaron Van Den Oord, Oriol Vinyals, et al · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Relational inductive biases, deep learning, and graph networks
Peter W Battaglia, Jessica B Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinicius Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, et al · 2018
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What is a cognitive map? organizing knowledge for flexible behavior
Timothy EJ Behrens, Timothy H Muller, James CR Whittington, Shirley Mark, Alon B Baram, Kimberly L Stachenfeld, and Zeb Kurth-Nelson · 2018
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A framework for the quantitative evaluation of disentangled representations
Cian Eastwood and Christopher K. I. Williams · 2018
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Matrix capsules with em routing
Geoffrey E Hinton, Sara Sabour, and Nicholas Frosst · 2018
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Disentangling by factorising
Hyunjik Kim and Andriy Mnih · 2018
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Tell me where to look: Guided attention inference network
Kunpeng Li, Ziyan Wu, Kuan-Chuan Peng, Jan Ernst, and Yun Fu · 2018
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Iterative amortized inference
Joe Marino, Yisong Yue, and Stephan Mandt · 2018
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Vae with a vampprior
Jakub Tomczak and Max Welling · 2018
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Monet: Unsupervised scene decomposition and representation
Christopher P Burgess, Loic Matthey, Nicholas Watters, Rishabh Kabra, Irina Higgins, Matt Botvinick, and Alexander Lerchner · 2019
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Genesis: Generative scene inference and sampling with object-centric latent representations
Martin Engelcke, Adam R Kosiorek, Oiwi Parker Jones, and Ingmar Posner · 2019
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Multi-object representation learning with iterative variational inference
Klaus Greff, Raphaël Lopez Kaufman, Rishabh Kabra, Nick Watters, Christopher Burgess, Daniel Zoran, Loic Matthey, Matthew Botvinick, and Alexander Lerchner · 2019
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Contrastive learning inverts the data generating process
Roland S Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, and Wieland Brendel · 2021
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Weakly supervised representation learning with sparse perturbations
Kartik Ahuja, Jason S Hartford, and Yoshua Bengio · 2022
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Interventional causal representation learning
Kartik Ahuja, Yixin Wang, Divyat Mahajan, and Yoshua Bengio · 2022
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Weakly supervised causal representation learning
Johann Brehmer, Pim De Haan, Phillip Lippe, and Taco S Cohen · 2022
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Function classes for identifiable nonlinear independent component analysis
Simon Buchholz, Michel Besserve, and Bernhard Schölkopf · 2022
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Nonlinear ica using auxiliary variables and generalized contrastive learning
Aapo Hyvarinen, Hiroaki Sasaki, and Richard Turner · 2019
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Nonlinear ica using auxiliary variables and generalized contrastive learning
Aapo Hyvarinen, Hiroaki Sasaki, and Richard Turner · 2019
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Multi-object datasets
Rishabh Kabra, Chris Burgess, Loic Matthey, Raphael Lopez Kaufman, Klaus Greff, Malcolm Reynolds, and Alexander Lerchner · 2019
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Challenging common assumptions in the unsupervised learning of disentangled representations
Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Raetsch, Sylvain Gelly, Bernhard Schölkopf, and Olivier Bachem · 2019
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Disentangling disentanglement in variational autoencoders
Emile Mathieu, Tom Rainforth, N Siddharth, and Yee Whye Teh · 2019
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Spriteworld: A flexible, configurable reinforcement learning environment
Nicholas Watters, Loic Matthey, Sebastian Borgeaud, Rishabh Kabra, and Alexander Lerchner · 2019
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Spatial broadcast decoder: A simple architecture for learning disentangled representations in vaes
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Michael Chang, Thomas L Griffiths, and Sergey Levine · 2022
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Savi++: Towards end-to-end object-centric learning from real-world videos
Gamaleldin Elsayed, Aravindh Mahendran, Sjoerd van Steenkiste, Klaus Greff, Michael C Mozer, and Thomas Kipf · 2022
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Slot order matters for compositional scene understanding
Patrick Emami, Pan He, Sanjay Ranka, and Anand Rangarajan · 2022
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How to represent part-whole hierarchies in a neural network
Geoffrey Hinton · 2022
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Identifiability of deep generative models without auxiliary information
Bohdan Kivva, Goutham Rajendran, Pradeep Ravikumar, and Bryon Aragam · 2022
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Object-centric causal representation learning
Amin Mansouri, Jason Hartford, Kartik Ahuja, and Yoshua Bengio · 2022
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Learning with capsules: A survey
Fabio De Sousa Ribeiro, Kevin Duarte, Miles Everett, Georgios Leontidis, and Mubarak Shah · 2022
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From statistical to causal learning
Bernhard Schölkopf and Julius von Kügelgen · 2022
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Illiterate dall-e learns to compose
Gautam Singh, Fei Deng, and Sungjin Ahn · 2022
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Neural block-slot representations
Gautam Singh, Yeongbin Kim, and Sungjin Ahn · 2022
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Simple unsupervised object-centric learning for complex and naturalistic videos
Gautam Singh, Yi-Fu Wu, and Sungjin Ahn · 2022
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Nonlinear ICA using volume-preserving transformations
Xiaojiang Yang, Yi Wang, Jiacheng Sun, Xing Zhang, Shifeng Zhang, Zhenguo Li, and Junchi Yan · 2022
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Provably learning object-centric representations
Jack Brady, Roland S Zimmermann, Yash Sharma, Bernhard Schölkopf, Julius von Kügelgen, and Wieland Brendel · 2023
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Grounded object centric learning
Avinash Kori, Francesco Locatello, Fabio De Sousa Ribeiro, Francesca Toni, and Ben Glocker · 2023
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Object-centric architectures enable efficient causal representation learning
Amin Mansouri, Jason Hartford, Yan Zhang, and Yoshua Bengio · 2023
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Bridging the gap to real-world object-centric learning
Maximilian Seitzer, Max Horn, Andrii Zadaianchuk, Dominik Zietlow, Tianjun Xiao, Carl-Johann Simon-Gabriel, Tong He, Zheng Zhang, Bernhard Schölkopf, Thomas Brox, et al · 2023
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Slot-vae: Object-centric scene generation with slot attention
Yanbo Wang, Letao Liu, and Justin Dauwels · 2023
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Slot-VAE: Object-centric scene generation with slot attention
Yanbo Wang, Letao Liu, and Justin Dauwels · 2023
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Spot: Self-training with patch-order permutation for object-centric learning with autoregressive transformers
Ioannis Kakogeorgiou, Spyros Gidaris, Konstantinos Karantzalos, and Nikos Komodakis · 2024
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