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03/31/2023
Learning Internal Representations of 3D Transformations from 2D Projected Inputs
When interacting in a three dimensional world, humans must estimate 3D s...
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10/15/2022
Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution
Neuroscience has long been an important driver of progress in artificial...
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09/30/2022
Minimalistic Unsupervised Learning with the Sparse Manifold Transform
We describe a minimalistic and interpretable method for unsupervised lea...
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09/07/2022
Bispectral Neural Networks
We present a novel machine learning architecture, Bispectral Neural Netw...
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09/30/2020
RG-Flow: A hierarchical and explainable flow model based on renormalization group and sparse prior
Flow-based generative models have become an important class of unsupervi...
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06/18/2020
Fully Test-time Adaptation by Entropy Minimization
Faced with new and different data during testing, a model must adapt its...
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08/08/2019
Dynamic Scale Inference by Entropy Minimization
Given the variety of the visual world there is not one true scale for re...
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05/26/2019
Auditory Separation of a Conversation from Background via Attentional Gating
We present a model for separating a set of voices out of a sound mixture...
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02/14/2019
Superposition of many models into one
We present a method for storing multiple models within a single set of p...
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03/23/2018
Generalization Challenges for Neural Architectures in Audio Source Separation
Recent work has shown that recurrent neural networks can be trained to s...
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03/23/2018
Convolutional vs. Recurrent Neural Networks for Audio Source Separation
Recent work has shown that recurrent neural networks can be trained to s...
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11/28/2016