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08/21/2023
Simple Cycle Reservoirs are Universal
Reservoir computation models form a subclass of recurrent neural network...
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06/04/2022
Interpretable Models Capable of Handling Systematic Missingness in Imbalanced Classes and Heterogeneous Datasets
Application of interpretable machine learning techniques on medical data...
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02/01/2021
Probabilistic Learning Vector Quantization on Manifold of Symmetric Positive Definite Matrices
In this paper, we develop a new classification method for manifold-value...
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12/28/2020
A Survey on Neural Network Interpretability
Along with the great success of deep neural networks, there is also grow...
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12/08/2020
A Geometric Framework for Pitch Estimation on Acoustic Musical Signals
This paper presents a geometric approach to pitch estimation (PE)-an imp...
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09/17/2020
LAAT: Locally Aligned Ant Technique for detecting manifolds of varying density
Dimensionality reduction and clustering are often used as preliminary st...
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05/07/2020
Visualisation and knowledge discovery from interpretable models
Increasing number of sectors which affect human lives, are using Machine...
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03/24/2020
Input representation in recurrent neural networks dynamics
Reservoir computing is a popular approach to design recurrent neural net...
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12/10/2019
Feature Relevance Determination for Ordinal Regression in the Context of Feature Redundancies and Privileged Information
Advances in machine learning technologies have led to increasingly power...
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07/15/2019
Dynamical Systems as Temporal Feature Spaces
Parameterized state space models in the form of recurrent networks are o...
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03/24/2019
Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets
Data augmentation is rapidly gaining attention in machine learning. Synt...
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03/24/2019
A mixture of experts model for predicting persistent weather patterns
Weather and atmospheric patterns are often persistent. The simplest weat...
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02/20/2019
Feature Relevance Bounds for Ordinal Regression
The increasing occurrence of ordinal data, mainly sociodemographic, led ...
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03/13/2017
Probabilistic Matching: Causal Inference under Measurement Errors
The abundance of data produced daily from large variety of sources has b...
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07/07/2016
A Classification Framework for Partially Observed Dynamical Systems
We present a general framework for classifying partially observed dynami...
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01/21/2016
Model-Coupled Autoencoder for Time Series Visualisation
We present an approach for the visualisation of a set of time series tha...
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05/05/2015
Autoencoding Time Series for Visualisation
We present an algorithm for the visualisation of time series. To that en...
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10/31/2012
Learning in the Model Space for Fault Diagnosis
The emergence of large scaled sensor networks facilitates the collection...
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11/09/2011