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05/26/2023
Efficient Decoding of Compositional Structure in Holistic Representations
We investigate the task of retrieving information from compositional dis...
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03/23/2023
Learning and generalization of compositional representations of visual scenes
Complex visual scenes that are composed of multiple objects, each with a...
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12/07/2022
Efficient Optimization with Higher-Order Ising Machines
A prominent approach to solving combinatorial optimization problems on p...
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08/28/2022
Computing with Hypervectors for Efficient Speaker Identification
We introduce a method to identify speakers by computing with high-dimens...
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04/23/2022
Learning and Inference in Sparse Coding Models with Langevin Dynamics
We describe a stochastic, dynamical system capable of inference and lear...
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03/02/2022
Integer Factorization with Compositional Distributed Representations
In this paper, we present an approach to integer factorization using dis...
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09/08/2021
Computing on Functions Using Randomized Vector Representations
Vector space models for symbolic processing that encode symbols by rando...
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06/17/2021
Generalized Learning Vector Quantization for Classification in Randomized Neural Networks and Hyperdimensional Computing
Machine learning algorithms deployed on edge devices must meet certain r...
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06/09/2021
Vector Symbolic Architectures as a Computing Framework for Nanoscale Hardware
This article reviews recent progress in the development of the computing...
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03/29/2021
Transformer visualization via dictionary learning: contextualized embedding as a linear superposition of transformer factors
Transformer networks have revolutionized NLP representation learning sin...
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07/07/2020
Resonator networks for factoring distributed representations of data structures
The ability to encode and manipulate data structures with distributed ne...
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10/09/2019
Word Embedding Visualization Via Dictionary Learning
Co-occurrence statistics based word embedding techniques have proved to ...
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06/19/2019
Resonator Circuits for factoring high-dimensional vectors
We describe a type of neural network, called a Resonator Circuit, that f...
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06/23/2018
The Sparse Manifold Transform
We present a signal representation framework called the sparse manifold...
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05/26/2016
DeepMovie: Using Optical Flow and Deep Neural Networks to Stylize Movies
A recent paper by Gatys et al. describes a method for rendering an image...
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12/20/2014
Discovering Hidden Factors of Variation in Deep Networks
Deep learning has enjoyed a great deal of success because of its ability...
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11/30/2010
Learning sparse representations of depth
This paper introduces a new method for learning and inferring sparse rep...
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01/07/2010
