A Cloud-based Framework for Implementing Portable Machine Learning Pipelines for Neural Data Analysis. - Charles A. Ellis; Ping Gu; Mohammad S. Eslampanah Sendi; Daniel E. Huddleston; Ashish Sharma 001; Babak Mahmoudi (EMBC, 2019)

A Novel Local Explainability Approach for Spectral Insight into Raw EEG-based Deep Learning Classifiers. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (BIBE, 2021)

A Gradient-based Approach for Explaining Multimodal Deep Learning Classifiers. - Charles A. Ellis; Rongen Zhang; Vince D. Calhoun; Darwin A. Carbajal; Robyn L. Miller; May D. Wang (BIBE, 2021)

A Novel Local Ablation Approach for Explaining Multimodal Classifiers. - Charles A. Ellis; Rongen Zhang; Vince D. Calhoun; Darwin A. Carbajal; Mohammad S. Eslampanah Sendi; May D. Wang; Robyn L. Miller (BIBE, 2021)

A Novel Activation Maximization-based Approach for Insight into Electrophysiology Classifiers. - Charles A. Ellis; Mohammad S. Eslampanah Sendi; Robyn L. Miller; Vince D. Calhoun (BIBM, 2021)

Explainable Sleep Stage Classification with Multimodal Electrophysiology Time-series*. - Charles A. Ellis; Rongen Zhang; Darwin A. Carbajal; Robyn L. Miller; Vince D. Calhoun; May D. Wang (EMBC, 2021)

Hierarchical Neural Network with Layer-wise Relevance Propagation for Interpretable Multiclass Neural State Classification. - Charles A. Ellis; Mohammad S. Eslampanah Sendi; Jon T. Willie; Babak Mahmoudi (NER, 2021)

Algorithm-Agnostic Explainability for Unsupervised Clustering. - Charles A. Ellis; Mohammad S. Eslampanah Sendi; Sergey M. Plis; Robyn L. Miller; Vince D. Calhoun (CoRR, 2021)

An Approach for Estimating Explanation Uncertainty in fMRI dFNC Classification. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (BIBE, 2022)

Examining Effects of Schizophrenia on EEG with Explainable Deep Learning Models. - Charles A. Ellis; Abhinav Sattiraju; Robyn L. Miller; Vince D. Calhoun (BIBE, 2022)

Examining Reproducibility of EEG Schizophrenia Biomarkers Across Explainable Machine Learning Models. - Charles A. Ellis; Abhinav Sattiraju; Robyn L. Miller; Vince D. Calhoun (BIBE, 2022)

Exploring Relationships between Functional Network Connectivity and Cognition with an Explainable Clustering Approach. - Charles A. Ellis; Martina Lapera Sancho; Mohammad S. Eslampanah Sendi; Robyn L. Miller; Vince D. Calhoun (BIBE, 2022)

A Model Visualization-based Approach for Insight into Waveforms and Spectra Learned by CNNs. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (EMBC, 2022)

An Unsupervised Feature Learning Approach for Elucidating Hidden Dynamics in rs-fMRI Functional Network Connectivity. - Charles A. Ellis; Mohammad S. Eslampanah Sendi; Robyn L. Miller; Vince D. Calhoun (EMBC, 2022)

A Systematic Approach for Explaining Time and Frequency Features Extracted by Convolutional Neural Networks From Raw Electroencephalography Data. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (Frontiers Neuroinformatics, 2022)

An Explainable and Robust Deep Learning Approach for Automated Electroencephalography-Based Schizophrenia Diagnosis. - Abhinav Sattiraju; Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (BIBE, 2023)

Improving Explainability for Single-Channel EEG Deep Learning Classifiers via Interpretable Filters and Activation Analysis. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (BIBM, 2023)

Improving Multichannel Raw Electroencephalography-based Diagnosis of Major Depressive Disorder via Transfer Learning with Single Channel Sleep Stage Data. - Charles A. Ellis; Abhinav Sattiraju; Robyn L. Miller; Vince D. Calhoun (BIBM, 2023)

A Novel Explainable Fuzzy Clustering Approach for fMRI Dynamic Functional Network Connectivity Analysis. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (EMBC, 2023)

A Convolutional Autoencoder-based Explainable Clustering Approach for Resting-State EEG Analysis. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (EMBC, 2023)

Neuropsychiatric Disorder Subtyping Via Clustered Deep Learning Classifier Explanations. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (EMBC, 2023)

Novel Approach Explains Spatio-Spectral Interactions In Raw Electroencephalogram Deep Learning Classifiers. - Charles A. Ellis; Abhinav Sattiraju; Robyn L. Miller; Vince D. Calhoun (ICASSP Workshops, 2023)

Identifying Neuropsychiatric Disorder Subtypes and Subtype-Dependent Variation in Diagnostic Deep Learning Classifier Performance. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (ISBI, 2023)

Novel methods for elucidating modality importance in multimodal electrophysiology classifiers. - Charles A. Ellis; Mohammad S. Eslampanah Sendi; Rongen Zhang; Darwin A. Carbajal; May D. Wang; Robyn L. Miller; Vince D. Calhoun (Frontiers Neuroinformatics, 2023)

Evaluating Augmentation Approaches for Deep Learning-based Major Depressive Disorder Diagnosis with Raw Electroencephalogram Data. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (EMBC, 2024)

Identifying Reproducibly Important EEG Markers of Schizophrenia with an Explainable Multi-Model Deep Learning Approach. - Martina Lapera Sancho; Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (EMBC, 2024)

Uncovering Effects of Schizophrenia upon a Maximally Significant, Minimally Complex Subset of Default Mode Network Connectivity Features. - Masoud Seraji; Charles A. Ellis; Mohammad S. Eslampanah Sendi; Robyn L. Miller; Vince D. Calhoun (EMBC, 2024)

Cross-Sampling Rate Transfer Learning for Enhanced Raw EEG Deep Learning Classifier Performance in Major Depressive Disorder Diagnosis. - Charles A. Ellis; Robyn L. Miller; Vince D. Calhoun (ISBI, 2024)

Improving Age Prediction: Utilizing LSTM-Based Dynamic Forecasting For Data Augmentation in Multivariate Time Series Analysis. - Yutong Gao 002; Charles A. Ellis; Vince D. Calhoun; Robyn L. Miller (SSIAI, 2024)

Identifying EEG Biomarkers of Depression with Novel Explainable Deep Learning Architectures. - Charles A. Ellis; Martina Lapera Sancho; Robyn L. Miller; Vince D. Calhoun (xAI (4), 2024)

Multimodal MRI-based Detection of Amyloid Status in Alzheimer's Disease Continuum. - Giorgio Dolci; Charles A. Ellis; Federica Cruciani; Lorenza Brusini; Anees Abrol; Ilaria Boscolo Galazzo; Gloria Menegaz; Vince D. Calhoun (CoRR, 2024)

Decentralized ComBat-Mega for Harmonizing FNC Data in Coinstac. - Sunitha Basodi; Charles A. Ellis; Biozid Bostami; Frank G. Hillary; Sandeep R. Panta; Vince D. Calhoun (ISBI, 2025)