Stephen Jose Hanson

According to our database, Stephen Jose Hanson authored at least 42 papers between 1983 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Causally informed activity flow models provide mechanistic insight into network-generated cognitive activations.

Ruben Sanchez-Romero, Takuya Ito, Ravi D. Mill, Stephen José Hanson, Michael W. Cole

NeuroImage, September, 2023

Dense Sample Deep Learning.

Stephen José Hanson, Vivek Yadav, Catherine Hanson

CoRR, 2023

2021

Uncovering the Metricity of Representational Spaces in the Brain: Evidence from Colors and Letters.

Leyla Roksan Caglar, Catherine Hanson, Stephen José Hanson

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

2020

The Stochastic Delta Rule: Faster and More Accurate Deep Learning Through Adaptive Weight Noise.

Noah Frazier-Logue, Stephen José Hanson

Neural Comput., 2020

Computations and Connectivity Underlying Aversive Counterfactuals.

Colleen Mills-Finnerty, Catherine Hanson, Mohannad Khadr, Stephen José Hanson

Brain Connect., 2020

2018

Dropout is a special case of the stochastic delta rule: faster and more accurate deep learning.

Noah Frazier-Logue, Stephen José Hanson

CoRR, 2018

2016

Deep Learning and Attentional Bias in Human Category Learning.

Leyla Roksan Caglar, Stephen Jose Hanson

Proceedings of the 38th Annual Meeting of the Cognitive Science Society, 2016

2014

Brain network response underlying decisions about abstract reinforcers.

Colleen Mills-Finnerty, Catherine Hanson, Stephen Jose Hanson

NeuroImage, 2014

Seeing is Worse than Believing: Reading People's Minds Better than Computer-Vision Methods Recognize Actions.

Andrei Barbu, Daniel Paul Barrett, Wei Chen, Siddharth Narayanaswamy, Caiming Xiong, Jason J. Corso, Christiane D. Fellbaum, Catherine Hanson, Stephen José Hanson, Sébastien Hélie, Evguenia Malaia, Barak A. Pearlmutter, Jeffrey Mark Siskind, Thomas Michael Talavage, Ronnie B. Wilbur

Proceedings of the Computer Vision - ECCV 2014, 2014

2013

A Study of Actor and Action Semantic retention in Video Supervoxel Segmentation.

Chenliang Xu, Richard F. Doell, Stephen José Hanson, Catherine Hanson, Jason J. Corso

Int. J. Semantic Comput., 2013

Transmodal Analysis of Neural Signals.

Yaroslav O. Halchenko, Michael Hanke, James V. Haxby, Stephen Jose Hanson, Christoph S. Herrmann

CoRR, 2013

Atypical Effective Connectivity of Social Brain Networks in Individuals with Autism.

Catherine Hanson, Stephen José Hanson, Joseph D. Ramsey, Clark Glymour

Brain Connect., 2013

Are Actor and Action Semantics Retained in Video Supervoxel Segmentation?

Chenliang Xu, Richard F. Doell, Stephen Jose Hanson, Catherine Hanson, Jason J. Corso

Proceedings of the 2013 IEEE Seventh International Conference on Semantic Computing, 2013

2011

Multi-subject search correctly identifies causal connections and most causal directions in the DCM models of the Smith et al. simulation study.

Joseph D. Ramsey, Stephen José Hanson, Clark Glymour

NeuroImage, 2011

High-resolution imaging of the fusiform face area (FFA) using multivariate non-linear classifiers shows diagnosticity for non-face categories.

Stephen José Hanson, Arielle Schmidt

NeuroImage, 2011

2010

Six problems for causal inference from fMRI.

Joseph D. Ramsey, Stephen José Hanson, Catherine Hanson, Yaroslav O. Halchenko, Russell A. Poldrack, Clark Glymour

NeuroImage, 2010

2009

PyMVPA: a Python Toolbox for Multivariate Pattern Analysis of fMRI Data.

Michael Hanke, Yaroslav O. Halchenko, Per B. Sederberg, Stephen José Hanson, James V. Haxby, Stefan Pollmann

Neuroinformatics, 2009

Solving the brain synchrony eigenvalue problem: conservation of temporal dynamics (fMRI) over subjects doing the same task.

Stephen José Hanson, Alessandro D. Gagliardi, Catherine Hanson

J. Comput. Neurosci., 2009

PyMVPA: a unifying approach to the analysis of neuroscientific data.

Michael Hanke, Yaroslav O. Halchenko, Per B. Sederberg, Emanuele Olivetti, Ingo Fründ, Jochem W. Rieger, Christoph S. Herrmann, James V. Haxby, Stephen José Hanson, Stefan Pollmann

Frontiers Neuroinformatics, 2009

2008

Brain Reading Using Full Brain Support Vector Machines for Object Recognition: There Is No "Face" Identification Area.

Stephen Jose Hanson, Yaroslav O. Halchenko

Neural Comput., 2008

2004

The RUMBA software - Tools for neuroimaging data analysis.

Benjamin Martin Bly, Donovan Rebbechi, Stephen Jose Hanson, Giorgio Grasso

Neuroinformatics, 2004

Combinatorial codes in ventral temporal lobe for object recognition: Haxby (2001) revisited: is there a "face" area?

Stephen José Hanson, Toshihiko Matsuka, James V. Haxby

NeuroImage, 2004

Irresistibly Attractive Fruitless Feature Dimensions.

Toshihiko Matsuka, James E. Corter, Stephen Jose Hanson

Proceedings of the International Conference on Cognitive Modelling, 2004

2002

On the Emergence of Rules in Neural Networks.

Stephen Jose Hanson, Michiro Negishi

Neural Comput., 2002

2001

Grammar Transfer in a Second Order Recurrent Neural Network.

Michiro Negishi, Stephen Jose Hanson

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Connectionist Neuroimaging.

Stephen José Hanson, Michiro Negishi, Catherine Hanson

Proceedings of the Emergent Neural Computational Architectures Based on Neuroscience, 2001

2000

Nonlinear Autoassociation Is Not Equivalent to PCA.

Nathalie Japkowicz, Stephen Jose Hanson, Mark A. Gluck

Neural Comput., 2000

1999

Adaptability of the backpropagation procedure.

Nathalie Japkowicz, Stephen Jose Hanson

Proceedings of the International Joint Conference Neural Networks, 1999

1998

Michael Arbib's The Metaphorical Brain 2: The Sequel?

Stephen Jose Hanson

Artif. Intell., 1998

1995

A Neural Network Autoassociator for Induction Motor Failure Prediction.

Thomas Petsche, Angelo Marcantonio, Christian Darken, Stephen Jose Hanson, Gary M. Kuhn, N. Iwan Santoso

Proceedings of the Advances in Neural Information Processing Systems 8, 1995

1994

Using Neural Networks to Modularize Software.

Robert W. Schwanke, Stephen Jose Hanson

Mach. Learn., 1994

1993

Strategic Directions in Machine Learning.

Stephen Jose Hanson, Werner Remmele, Ronald L. Rivest

Proceedings of the Machine Learning: From Theory to Applications, 1993

Introduction.

Stephen Jose Hanson

Proceedings of the Machine Learning: From Theory to Applications, 1993

1990

Spherical Units as Dynamic Consequential Regions.

Stephen Jose Hanson, Mark A. Gluck

Proceedings of the Advances in Neural Information Processing Systems 3, 1990

1989

Conceptual Clustering, Categorization, and Polymorphy.

Stephen Jose Hanson, Malcolm Bauer

Mach. Learn., 1989

Meiosis Networks.

Stephen Jose Hanson

Proceedings of the Advances in Neural Information Processing Systems 2, 1989

1988

Comparing Biases for Minimal Network Construction with Back-Propagation.

Stephen Jose Hanson, Lorien Y. Pratt

Proceedings of the Advances in Neural Information Processing Systems 1, 1988

1987

Minkowski-r Back-Propagation: Learning in Connectionist Models with Non-Euclidian Error Signals.

Stephen Jose Hanson, David J. Burr

Proceedings of the Neural Information Processing Systems, Denver, Colorado, USA, 1987, 1987

1985

Programmer Perceptions of Productivity and Programming Tools.

Stephen Jose Hanson, Richard R. Rosinski

Commun. ACM, 1985

Machine Learning, Clustering and Polymorphy.

Stephen Jose Hanson, Malcolm Bauer

Proceedings of the UAI '85: Proceedings of the First Annual Conference on Uncertainty in Artificial Intelligence, 1985

1984

Interface Design and Multivariate Analysis of UNIX Command Use.

Stephen Jose Hanson, Robert E. Kraut, James M. Farber

ACM Trans. Inf. Syst., 1984

1983

Command use and interface design.

Robert E. Kraut, Stephen José Hanson, James M. Farber

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 1983