A. Skabar

发表

Direction‐of‐Change Financial Time Series Forecasting using a Similarity‐Based Classification Model

Andrew Skabar, A. Skabar, 2013 .

Mineral Prospectivity Prediction from High-Dimensional Geoscientific Data Using a Similarity-Based Density Estimation Model

A. Skabar, 2011 .

Single-Class Classification Augmented with Unlabeled Data: A Symbolic Approach

A. Skabar, 2003, Australian Conference on Artificial Intelligence.

Building adaptive and flexible individual-based ecological models for a changing world via pattern-guided evolution

A. Skabar, Sean Haythorne, 2012 .

An improved pattern-guided evolution approach for the development of adaptive individual-based ecological models

A. Skabar, Sean Haythorne, 2013 .

Density estimation-based document categorization using von Mises-Fisher kernels

Andrew Skabar, Shahmeer Memon, A. Skabar, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Mapping Mineralization Probabilities using Multilayer Perceptrons

Andrew Skabar, A. Skabar, 2005 .

Evolutionary Intelligence and Communication in Societies of Virtually Embodied Agents

Binh Nguyen, Andrew Skabar, A. Skabar, 2009, ACAL.

MODELING THE SPATIAL DISTRIBUTION OF MINERAL DEPOSITS USING NEURAL NETWORKS

Andrew Skabar, A. Skabar, 2007 .

Random vector generation from mixed-attribute datasets using random walk

Andrew Skabar, A. Skabar, 2016, 2016 Winter Simulation Conference (WSC).

Neural Networks and Financial Trading and the Efficient Markets Hypothesis

Andrew Skabar, Ian Cloete, A. Skabar, 2002, ACSC.

Sentence Level Clustering using Fuzzy Relational Algorithm

C. R. Barde, Snehal Raundal, A. Skabar, 2015 .

Mineral Potential Mapping Using Bayesian Learning for Multilayer Perceptrons

Andrew Skabar, A. Skabar, 2007 .

Automatic MLP Weight Regularization on Mineralization Prediction Tasks

Andrew Skabar, A. Skabar, 2005, KES.

Direction-of-Change Financial Time Series Forecasting Using Neural Networks: A Bayesian Approach

Andrew Skabar, A. Skabar, 2008, World Congress on Engineering.

Using Eigencentrality to Estimate Joint, Conditional and Marginal Probabilities from Mixed-Variable Data: Method and Applications pdf

Andrew Skabar, A. Skabar, 2018, ArXiv.

Graph-Based Collaborative Filtering Using Rating Nodes: A Solution to the High Ratings/Low Ratings Problem

Andrew Skabar, Alphan Culha, A. Skabar, 2015, Australasian Conference on Artificial Intelligence.

Restricted Boltzmann Machines: an Eigencentrality-based Approach

Andrew Skabar, A. Skabar, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Predicting the Distribution of Discrete Spatial Events Using Artificial Neural Networks

Andrew Skabar, A. Skabar, 2003, Australian Conference on Artificial Intelligence.

Mineral potential mapping using feed-forward neural networks

Andrew Skabar, A. Skabar, 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..