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06/02/2023
On Feature Diversity in Energy-based Models
Energy-based learning is a powerful learning paradigm that encapsulates ...
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01/03/2023
WLD-Reg: A Data-dependent Within-layer Diversity Regularizer
Neural networks are composed of multiple layers arranged in a hierarchic...
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09/22/2022
Efficient CNN with uncorrelated Bag of Features pooling
Despite the superior performance of CNN, deploying them on low computati...
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02/09/2022
Non-Linear Spectral Dimensionality Reduction Under Uncertainty
In this paper, we consider the problem of non-linear dimensionality redu...
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02/09/2022
Reducing Redundancy in the Bottleneck Representation of the Autoencoders
Autoencoders are a type of unsupervised neural networks, which can be us...
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11/10/2021
Learning to ignore: rethinking attention in CNNs
Recently, there has been an increasing interest in applying attention me...
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06/10/2021
Within-layer Diversity Reduces Generalization Gap
Neural networks are composed of multiple layers arranged in a hierarchic...
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09/01/2020
Graph Embedding with Data Uncertainty
spectral-based subspace learning is a common data preprocessing step in ...
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07/20/2020
Monte Carlo Dropout Ensembles for Robust Illumination Estimation
Computational color constancy is a preprocessing step used in many camer...
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05/06/2020
Probabilistic Color Constancy
In this paper, we propose a novel unsupervised color constancy method, c...
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10/23/2019
INTEL-TAU: A Color Constancy Dataset
In this paper, we describe a new large dataset for illumination estimati...
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06/11/2019
Bag of Color Features For Color Constancy
In this paper, we propose a novel color constancy approach, called Bag o...
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06/04/2019