James V. Stone

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A Vector Matrix Tutorial

James V. Stone, 2004 .

Principal Component Analysis for Preprocessing Data

James V. Stone, 2004 .

A Learning Rule for Extracting Temporal Invariances

James V. Stone, Alistair J. Bray, 1995, IWANN.

Independent Component Analysis: A Tutorial Introduction

James V. Stone, 2007 .

Projection Pursuit Gradient Ascent

James V. Stone, 2004 .

Information Theory: A Tutorial Introduction pdf

James V. Stone, 2015, ArXiv.

Seeing : the computational approach to biological vision

John P. Frisby, James V. Stone, J. Frisby, 2010 .

The Adaptive Bisector Method: Separating Slant and Tilt in Estimating Shape from Texture

James V. Stone, 1992, BMVC.

Blind deconvolution using temporal predictability

James V. Stone, 2002, Neurocomputing.

Learning Perceptually Salient Visual Parameters Using Spatiotemporal Smoothness Constraints

James V. Stone, 1996, Neural Computation.

Projection Pursuit: Stepwise Separation of Sources

James V. Stone, 2004 .

Adaptive Scale Filtering: A General Method for Obtaining Shape From Texture

James V. Stone, Stephen D. Isard, S. Isard, 1995, IEEE Trans. Pattern Anal. Mach. Intell..

Climbing Mount AI

James V. Stone, 2019 .

Strategies for Blind Source Separation

James V. Stone, 2004 .

Seeing, Second Edition: The Computational Approach to Biological Vision

John P. Frisby, James V. Stone, J. Frisby, 2010 .

Complexity Pursuit Gradient Ascent

James V. Stone, 2004 .

Using reaction times and binary responses to estimate psychophysical performance: an information theoretic analysis

James V. Stone, 2014, Front. Neurosci..

Blind Source Separation Using Temporal Predictability

James V. Stone, 2001, Neural Computation.

Free-Lunch Learning: Modeling Spontaneous Recovery of Memory

James V. Stone, Peter E. Jupp, P. Jupp, 2007, Neural Computation.

A Self-Organising Model of Thermoregulatory Huddling

James V. Stone, Roderich Groß, Stuart P. Wilson, 2015, PLoS Comput. Biol..

Analysis of Optical Imaging Data Using Weak Models and ICA

John Porrill, John E. W. Mayhew, James V. Stone, 2000 .

Methods for Blind Source Separation

James V. Stone, 2004 .

Independent Component Analysis and Blind Source Separation

James V. Stone, 2004 .

Applications of ICA

James V. Stone, 2004 .

Unicycling Helps Your French: Spontaneous Recovery of Associations by Learning Unrelated Tasks

Inman Harvey, James V. Stone, 1996, Neural Computation.

Learning Spatio-Temporal Invariances

James V. Stone, 1994, BMVC.

Distributed Representations Accelerate Evolution of Adaptive Behaviours

James V. Stone, 2007, PLoS Comput. Biol..

Bayes' Rule: A Tutorial Introduction to Bayesian Analysis

James V. Stone, 2013 .

Falling towards Forgetfulness: Synaptic Decay Prevents Spontaneous Recovery of Memory

James V. Stone, Peter E. Jupp, P. Jupp, 2008, PLoS Comput. Biol..

Shape from Texture: Textural Invariance and the Problem of Scale in Perspective Images of Textured Surfaces

James V. Stone, 1990 .

A learning rule for extracting spatio-temporal invariances

James V. Stone, Alistair J. Bray, 1995 .

Decorrelation control by the cerebellum achieves oculomotor plant compensation in simulated vestibulo-ocular reflex

James V. Stone, P. Dean, J. Porrill, 2002, Proceedings of the Royal Society of London. Series B: Biological Sciences.

Recurrent cerebellar architecture solves the motor-error problem

James V. Stone, P. Dean, J. Porrill, 2004, Proceedings of the Royal Society of London. Series B: Biological Sciences.

Temporal Constraints on Visual Learning: A Computational Model

James V. Stone, N. Harper, N. Harper, 1999, Perception.

Spatiotemporal Independent Component Analysis of Event-Related fMRI Data Using Skewed Probability Density Functions

James V. Stone, J. Porrill, N. Porter, 2002, NeuroImage.

Independent component analysis: an introduction

James V. Stone, 2002, Trends in Cognitive Sciences.

When is now? Perception of simultaneity

James V. Stone, J. Porrill, N. Porter, 2001, Proceedings of the Royal Society of London. Series B: Biological Sciences.

Object recognition using spatiotemporal signatures

James V. Stone, 1998, Vision Research.

The Optimal Elastic Net: Finding Solutions to the Travelling Salesman Problem

James V. Stone, 1992 .

Unsupervised discovery of invariances

James V. Stone, Alistair J. Bray, S. Eglen, 1997 .

Vision and Brain: How We Perceive the World

James V. Stone, 2012 .

How self-organization can guide evolution

James V. Stone, Stuart P. Wilson, J. Glancy, 2016, Royal Society Open Science.

Marr: An Appreciation

James V. Stone, J. Frisby, 2012, Perception.

Footprints Sticking Out of the Sand. Part 2: Children's Bayesian Priors for Shape and Lighting Direction

James V. Stone, 2011, Perception.

On the relative time complexities of standard and conjugate gradient backpropagation

James V. Stone, R. Lister, 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

Determinants of object recognition

James V. Stone, D. Buckley, Felicity A Moger, 2000, Vision Research.

Independent Component Analysis

James V. Stone, 2015 .

Independent Components Analysis

James V. Stone, 2014 .

Independent Component Analysis

James V. Stone, E. Oja, J. Karhunen, 2015, Encyclopedia of Biometrics.

Visual awareness and the cerebellum: possible role of decorrelation control.

John Porrill, James V. Stone, James V Stone, 2004, Progress in brain research.

Object recognition: view-specificity and motion-specificity

James V. Stone, James V. Stone, 1999, Vision Research.

Computer Vision: What Is the Object? 1 Object Identiication in Human and Computer Vision

James V. Stone, 1993 .

Can artificial neural networks discover useful regularities

James V. Stone, C. J. Thorton, 1995 .

Making connections about brain connectivity

James V. Stone, Rolf Kötter, R. Kötter, 2002, Trends in Cognitive Sciences.

Where is the light? Bayesian perceptual priors for lighting direction

James V. Stone, J Porrill, J. Porrill, 2009, Proceedings of the Royal Society B: Biological Sciences.

Free-lunch learning and directional distributions in artificial neural networks

James V. Stone, P. Jupp, 2008 .

Error functions, error signals, and conjugate gradient back propagation

James V. Stone, Raymond Lister, 1995 .

Shape from local and global analysis of texture

James V. Stone, 1993 .

Learning stereo disparity using temporal smoothness constraints: a computational model.

James V. Stone, 1996, Spatial vision.

Independent Components Analysis for Step-wise Separation of Signals

James V. Stone, J. Porrill, 1997 .

The Adaptive Bisector Method: Separating Slant and Tilt in Estimating Shape from Texture*

James V. Stone, 1992 .

Who's the Daddy? Infidelity Favours Father-Son Facial Dissimilarity

James V. Stone, 2021, 2109.10848.

The Future of the Caribou Eskimos

James V. Stone, W. Oswalt, 1960 .

ETHNOGRAPHY AND ETHNOLOGY: Alaska Natives and the Land. Federal Field Committee for Development Planning in Alaska

James V. Stone, 1970 .

A Canonical Microfunction for Learning Perceptual Invariances

James V. Stone, J V Stone, 1996, Perception.

Hierachical learning of visual invariances via spatio-temporal constraints

James V. Stone, 1995 .

An empirical study of the time complexity of various error functions with conjugate gradient backpropagation

James V. Stone, R. Lister, J. V. Stone, 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

Bayes' Rule: A Tutorial Introduction to Bayesian Analysis

James V. Stone, 2013 .