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Endowing machines with abstract reasoning ability has been a long-term research topic in artificial intelligence.
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Raven’s progressive matrices and vocabulary scales , volume 759
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The number sense: How the mind creates mathematics
Stanislas Dehaene · 2011
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One shot learning of simple visual concepts
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Neural networks for machine learning lecture 6a overview of mini-batch gradient descent
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Learning structured output representation using deep conditional generative models
Kihyuk Sohn, Honglak Lee, and Xinchen Yan · 2015
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Learning structured output representation using deep conditional generative models
Kihyuk Sohn, Honglak Lee, and Xinchen Yan · 2015
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On implementing 2d rectangular assignment algorithms
David F Crouse · 2016
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Ladder variational autoencoders
Casper Kaae Sønderby, Tapani Raiko, Lars Maaløe, Søren Kaae Sønderby, and Ole Winther · 2016
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Categorical reparameterization with gumbel-softmax
Eric Jang, Shixiang Gu, and Ben Poole · 2016
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Towards a neural statistician
Harrison Edwards and Amos Storkey · 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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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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Measuring abstract reasoning in neural networks
David Barrett, Felix Hill, Adam Santoro, Ari Morcos, and Timothy Lillicrap · 2018
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Neural scene representation and rendering
SM Ali Eslami, Danilo Jimenez Rezende, Frederic Besse, Fabio Viola, Ari S Morcos, Marta Garnelo, Avraham Ruderman, Andrei A Rusu, Ivo Danihelka, Karol Gregor, et al · 2018
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Neural processes
Marta Garnelo, Jonathan Schwarz, Dan Rosenbaum, Fabio Viola, Danilo J Rezende, SM Eslami, and Yee Whye Teh · 2018
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The variational homoencoder: Learning to learn high capacity generative models from few examples
Luke B Hewitt, Maxwell I Nye, Andreea Gane, Tommi S Jaakkola, and Joshua B Tenenbaum · 2018
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Improving generalization for abstract reasoning tasks using disentangled feature representations
Xander Steenbrugge, Sam Leroux, Tim Verbelen, and Bart Dhoedt · 2018
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Yuhuai Wu, Honghua Dong, Roger Grosse, and Jimmy Ba · 2020
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Generating correct answers for progressive matrices intelligence tests
Niv Pekar, Yaniv Benny, and Lior Wolf · 2020
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Scale-localized abstract reasoning
Yaniv Benny, Niv Pekar, and Lior Wolf · 2021
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Roots: Object-centric representation and rendering of 3d scenes
Chang Chen, Fei Deng, and Sungjin Ahn · 2021
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Hierarchical few-shot generative models
Giorgio Giannone and Ole Winther · 2021
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Measuring abstract reasoning in neural networks
David Barrett, Felix Hill, Adam Santoro, Ari Morcos, and Timothy Lillicrap · 2018
Cited alongside, same era.
Recasting gradient-based meta-learning as hierarchical bayes
Erin Grant, Chelsea Finn, Sergey Levine, Trevor Darrell, and Thomas Griffiths · 2018
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On the measure of intelligence
François Chollet · 2019
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Attention on abstract visual reasoning
Lukas Hahne, Timo Lüddecke, Florentin Wörgötter, and David Kappel · 2019
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Attentive neural processes
Hyunjik Kim, Andriy Mnih, Jonathan Schwarz, Marta Garnelo, Ali Eslami, Dan Rosenbaum, Oriol Vinyals, and Yee Whye Teh · 2019
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Are disentangled representations helpful for abstract visual reasoning?
Sjoerd Van Steenkiste, Francesco Locatello, Jürgen Schmidhuber, and Olivier Bachem · 2019
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Abstract diagrammatic reasoning with multiplex graph networks
Duo Wang, Mateja Jamnik, and Pietro Lio · 2019
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Sheng Hu, Yuqing Ma, Xianglong Liu, Yanlu Wei, and Shihao Bai · 2021
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Simone: View-invariant, temporally-abstracted object representations via unsupervised video decomposition
Rishabh Kabra, Daniel Zoran, Goker Erdogan, Loic Matthey, Antonia Creswell, Matt Botvinick, Alexander Lerchner, and Chris Burgess · 2021
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Abstraction and analogy-making in artificial intelligence
Melanie Mitchell · 2021
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Dynamic inference with neural interpreters
Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi, Peter Gehler, Yoshua Bengio, Francesco Locatello, and Bernhard Schölkopf · 2021
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Raven’s progressive matrices completion with latent gaussian process priors
Fan Shi, Bin Li, and Xiangyang Xue · 2021
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Effective abstract reasoning with dual-contrast network
Tao Zhuo and Mohan Kankanhalli · 2021
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Stratified rule-aware network for abstract visual reasoning
Sheng Hu, Yuqing Ma, Xianglong Liu, Yanlu Wei, and Shihao Bai · 2021
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Dynamic inference with neural interpreters
Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi, Peter Gehler, Yoshua Bengio, Francesco Locatello, and Bernhard Schölkopf · 2021
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Raven’s progressive matrices completion with latent gaussian process priors
Fan Shi, Bin Li, and Xiangyang Xue · 2021
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Unsupervised learning of compositional scene representations from multiple unspecified viewpoints
Jinyang Yuan, Bin Li, and Xiangyang Xue · 2022
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Compositional law parsing with latent random functions
Fan Shi, Bin Li, and Xiangyang Xue · 2022
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Time-conditioned generative modeling of object-centric representations for video decomposition and prediction
Chengmin Gao and Bin Li · 2023
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Human-like systematic generalization through a meta-learning neural network
Brenden M Lake and Marco Baroni · 2023
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Compositional law parsing with latent random functions
Fan Shi, Bin Li, and Xiangyang Xue · 2023
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Compositional scene representation learning via reconstruction: A survey
Jinyang Yuan, Tonglin Chen, Bin Li, and Xiangyang Xue · 2023
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Human-like systematic generalization through a meta-learning neural network
Brenden M Lake and Marco Baroni · 2023
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Unsupervised object-centric learning from multiple unspecified viewpoints
Jinyang Yuan, Tonglin Chen, Zhimeng Shen, Bin Li, and Xiangyang Xue · 2024
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