2020

Solving Raven's Progressive Matrices with Neural Networks

Zhuo, Tao, Kankanhalli, Mohan

Understand

Raven's Progressive Matrices (RPM) have been widely used for Intelligence Quotient (IQ) test of humans.

In this paper, we aim to solve RPM with neural networks in both supervised and unsupervised manners.
First, we investigate strategies to reduce over-fitting in supervised learning.
We suggest the use of a neural network with deep layers and pre-training on large-scale datasets to improve model generalization.

Built on

Progressive matrices
John C. Raven · 1938
Earlier work this paper cites.
What one intelligence test measures: a theoretical account of the processing in the raven progressive matrices test
Patricia A Carpenter, Marcel A Just, and Peter Shell · 1990
Earlier work this paper cites.
The raven’s progressive matrices: change and stability over culture and time
John Raven · 2000
Earlier work this paper cites.
Psychological testing: An introduction
George Domino and Marla L Domino · 2006
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Addressing the raven’s progressive matrices test of “general” intelligence
Maithilee Kunda, Keith McGreggor, and Ashok Goel · 2009
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Confident reasoning on raven’s progressive matrices tests
Keith McGreggor and Ashok Goel · 2014
Earlier work this paper cites.
Fractals and ravens
Keith McGreggor, Maithilee Kunda, and Ashok Goel · 2014
Earlier work this paper cites.
Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
Earlier work this paper cites.
Vqa: Visual question answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C Lawrence Zitnick, and Devi Parikh · 2015
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Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
Earlier work this paper cites.

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Then

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