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03/16/2022
Understanding robustness and generalization of artificial neural networks through Fourier masks
Despite the enormous success of artificial neural networks (ANNs) in man...
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10/18/2021
Interpolating between sampling and variational inference with infinite stochastic mixtures
Sampling and Variational Inference (VI) are two large families of method...
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10/13/2021
Two-argument activation functions learn soft XOR operations like cortical neurons
Neurons in the brain are complex machines with distinct functional compa...
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07/12/2021
Generalization of graph network inferences in higher-order probabilistic graphical models
Probabilistic graphical models provide a powerful tool to describe compl...
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05/03/2021
AvaTr: One-Shot Speaker Extraction with Transformers
To extract the voice of a target speaker when mixed with a variety of ot...
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12/10/2020
Flexible Few-Shot Learning with Contextual Similarity
Existing approaches to few-shot learning deal with tasks that have persi...
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11/11/2019
Learning From Brains How to Regularize Machines
Despite impressive performance on numerous visual tasks, Convolutional N...
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08/13/2019
Inverse Rational Control with Partially Observable Continuous Nonlinear Dynamics
Continuous control and planning remains a major challenge in robotics an...
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05/31/2019
Improved memory in recurrent neural networks with sequential non-normal dynamics
Training recurrent neural networks (RNNs) is a hard problem due to degen...
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02/02/2019
Belief dynamics extraction
Animal behavior is not driven simply by its current observations, but is...
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05/24/2018
Inverse POMDP: Inferring What You Think from What You Do
Complex behaviors are often driven by an internal model, which integrate...
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03/21/2018
Inference in Probabilistic Graphical Models by Graph Neural Networks
A useful computation when acting in a complex environment is to infer th...
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03/16/2018
Reviving and Improving Recurrent Back-Propagation
In this paper, we revisit the recurrent back-propagation (RBP) algorithm...
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01/31/2017
Skip Connections Eliminate Singularities
Skip connections made the training of very deep networks possible and ha...
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06/02/2011
