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05/30/2023
Compositional diversity in visual concept learning
Humans leverage compositionality to efficiently learn new concepts, unde...
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06/25/2020
Learning Task-General Representations with Generative Neuro-Symbolic Modeling
A hallmark of human intelligence is the ability to interact directly wit...
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03/19/2020
Generating new concepts with hybrid neuro-symbolic models
Human conceptual knowledge supports the ability to generate novel yet hi...
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07/15/2019
Robust Nonlinear Component Estimation with Tikhonov Regularization
Learning reduced component representations of data using nonlinear trans...
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03/05/2019
Learning a smooth kernel regularizer for convolutional neural networks
Modern deep neural networks require a tremendous amount of data to train...
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02/08/2018
Learning Inductive Biases with Simple Neural Networks
People use rich prior knowledge about the world in order to efficiently ...
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03/01/2017
Detecting Adversarial Samples from Artifacts
Deep neural networks (DNNs) are powerful nonlinear architectures that ar...
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10/03/2016