Pamela K. Douglas

Orcid: 0000-0003-2277-7526

According to our database1, Pamela K. Douglas authored at least 18 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Towards a white matter ephaptic coupling model of 1/f spectra.
Proceedings of the 12th International Winter Conference on Brain-Computer Interface, 2024

2023
Preventing antisocial robots: A pathway to artificial empathy.
Sci. Robotics, July, 2023

Visual Episodic Memory-based Exploration.
Proceedings of the Thirty-Sixth International Florida Artificial Intelligence Research Society Conference, 2023

2022
Diurnal variations of resting-state fMRI data: A graph-based analysis.
NeuroImage, 2022

Triadic Temporal Exponential Random Graph Models (TTERGM).
CoRR, 2022

Leveraging Evolutionary Algorithms for Feasible Hexapod Locomotion Across Uneven Terrain.
Proceedings of the Thirty-Fifth International Florida Artificial Intelligence Research Society Conference, 2022

2020
On the Similarity of Deep Learning Representations Across Didactic and Adversarial Examples.
CoRR, 2020

2019
Feature Fallacy: Complications with Interpreting Linear Decoding Weights in fMRI.
Proceedings of the Explainable AI: Interpreting, 2019

Reconsidering Spatial Priors In EEG Source Estimation : Does White Matter Contribute to EEG Rhythms?
Proceedings of the 7th International Winter Conference on Brain-Computer Interface, 2019

2016
Dynamic causal modelling of electrographic seizure activity using Bayesian belief updating.
NeuroImage, 2016

Decoding the Encoding of Functional Brain Networks: an fMRI Classification Comparison of Non-negative Matrix Factorization (NMF), Independent Component Analysis (ICA), and Sparse Coding Algorithms.
CoRR, 2016

2015
Characterising seizures in anti-NMDA-receptor encephalitis with dynamic causal modelling.
NeuroImage, 2015

2014
The utility of data-driven feature selection: Re: Chu et al. 2012.
NeuroImage, 2014

Non-negative matrix factorization of multimodal MRI, fMRI and phenotypic data reveals differential changes in default mode subnetworks in ADHD.
NeuroImage, 2014

2013
Balancing Clinical and Pathologic Relevance in the Machine Learning Diagnosis of Epilepsy.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

2011
Performance comparison of machine learning algorithms and number of independent components used in fMRI decoding of belief vs. disbelief.
NeuroImage, 2011

Large sample group independent component analysis of functional magnetic resonance imaging using anatomical atlas-based reduction and bootstrapped clustering.
Int. J. Imaging Syst. Technol., 2011

Real-Time Functional MRI Classification of Brain States Using Markov-SVM Hybrid Models: Peering Inside the rt-fMRI Black Box.
Proceedings of the Machine Learning and Interpretation in Neuroimaging, 2011


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