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The challenge in learning abstract concepts from images in an unsupervised fashion lies in the required integration of visual perception and generalizable relational reasoning.
The" wake-sleep" algorithm for unsupervised neural networks
Geoffrey E Hinton, Peter Dayan, Brendan J Frey, and Radford M Neal · 1995
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The aleph manual, 2001
Ashwin Srinivasan · 2001
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Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Program synthesis using natural language
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Matej Balog, Alexander L Gaunt, Marc Brockschmidt, Sebastian Nowozin, and Daniel Tarlow · 2017
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Adam Santoro, David Raposo, David G Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, and Timothy Lillicrap · 2017
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Junkyung Kim, Matthew Ricci, and Thomas Serre · 2018
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Neural program synthesis from diverse demonstration videos
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Lazar Valkov, Dipak Chaudhari, Akash Srivastava, Charles Sutton, and Swarat Chaudhuri · 2018
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Kevin Ellis, Maxwell Nye, Yewen Pu, Felix Sosa, Josh Tenenbaum, and Armando Solar-Lezama · 2019
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Kandinsky patterns as iq-test for machine learning
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The neuro-symbolic concept learner: Interpreting scenes, words, and sentences from natural supervision
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Stefano Teso and Kristian Kersting · 2019
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Maxwell Nye, Armando Solar-Lezama, Josh Tenenbaum, and Brenden M Lake · 2020
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Enriching visual with verbal explanations for relational concepts–combining lime with aleph
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Ting Chen, Saurabh Saxena, Lala Li, David J. Fleet, and Geoffrey E. Hinton · 2022
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