Charles A. Ellis

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 27

Top Topics

Learning Models

Unsupervised Clustering

Top Venues

Publications

Giorgio Dolci, Charles A. Ellis, Federica Cruciani, Lorenza Brusini, Anees Abrol, Ilaria Boscolo Galazzo, Gloria Menegaz, Vince D. Calhoun
Multimodal MRI-based Detection of Amyloid Status in Alzheimer's Disease Continuum. CoRR (2024)
Yutong Gao, Charles A. Ellis, Vince D. Calhoun, Robyn L. Miller
Improving Age Prediction: Utilizing LSTM-Based Dynamic Forecasting For Data Augmentation in Multivariate Time Series Analysis. SSIAI (2024)
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
A Novel Explainable Fuzzy Clustering Approach for fMRI Dynamic Functional Network Connectivity Analysis. EMBC (2023)
Yutong Gao, Charles A. Ellis, Vince D. Calhoun, Robyn L. Miller
Improving age prediction: Utilizing LSTM-based dynamic forecasting for data augmentation in multivariate time series analysis. CoRR (2023)
Charles A. Ellis, Mohammad S. Eslampanah Sendi, Rongen Zhang, Darwin A. Carbajal, May D. Wang, Robyn L. Miller, Vince D. Calhoun
Novel methods for elucidating modality importance in multimodal electrophysiology classifiers. Frontiers Neuroinformatics 17 (2023)
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
Neuropsychiatric Disorder Subtyping Via Clustered Deep Learning Classifier Explanations. EMBC (2023)
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
A Convolutional Autoencoder-based Explainable Clustering Approach for Resting-State EEG Analysis. EMBC (2023)
Abhinav Sattiraju, Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
An Explainable and Robust Deep Learning Approach for Automated Electroencephalography-Based Schizophrenia Diagnosis. BIBE (2023)
Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, Vince D. Calhoun
Novel Approach Explains Spatio-Spectral Interactions In Raw Electroencephalogram Deep Learning Classifiers. ICASSP Workshops (2023)
Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, Vince D. Calhoun
Improving Multichannel Raw Electroencephalography-based Diagnosis of Major Depressive Disorder via Transfer Learning with Single Channel Sleep Stage Data. BIBM (2023)
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
Improving Explainability for Single-Channel EEG Deep Learning Classifiers via Interpretable Filters and Activation Analysis. BIBM (2023)
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
Identifying Neuropsychiatric Disorder Subtypes and Subtype-Dependent Variation in Diagnostic Deep Learning Classifier Performance. ISBI (2023)
Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, Vince D. Calhoun
Examining Reproducibility of EEG Schizophrenia Biomarkers Across Explainable Machine Learning Models. BIBE (2022)
Charles A. Ellis, Martina Lapera Sancho, Mohammad S. Eslampanah Sendi, Robyn L. Miller, Vince D. Calhoun
Exploring Relationships between Functional Network Connectivity and Cognition with an Explainable Clustering Approach. BIBE (2022)
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
A Model Visualization-based Approach for Insight into Waveforms and Spectra Learned by CNNs. EMBC (2022)
Charles A. Ellis, Mohammad S. Eslampanah Sendi, Robyn L. Miller, Vince D. Calhoun
An Unsupervised Feature Learning Approach for Elucidating Hidden Dynamics in rs-fMRI Functional Network Connectivity. EMBC (2022)
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
An Approach for Estimating Explanation Uncertainty in fMRI dFNC Classification. BIBE (2022)
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
A Systematic Approach for Explaining Time and Frequency Features Extracted by Convolutional Neural Networks From Raw Electroencephalography Data. Frontiers Neuroinformatics 16 (2022)
Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, Vince D. Calhoun
Examining Effects of Schizophrenia on EEG with Explainable Deep Learning Models. BIBE (2022)
Charles A. Ellis, Rongen Zhang, Darwin A. Carbajal, Robyn L. Miller, Vince D. Calhoun, May D. Wang
. EMBC (2021)
Charles A. Ellis, Rongen Zhang, Vince D. Calhoun, Darwin A. Carbajal, Robyn L. Miller, May D. Wang
A Gradient-based Approach for Explaining Multimodal Deep Learning Classifiers. BIBE (2021)
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
A Novel Local Explainability Approach for Spectral Insight into Raw EEG-based Deep Learning Classifiers. BIBE (2021)
Charles A. Ellis, Rongen Zhang, Vince D. Calhoun, Darwin A. Carbajal, Mohammad S. Eslampanah Sendi, May D. Wang, Robyn L. Miller
A Novel Local Ablation Approach for Explaining Multimodal Classifiers. BIBE (2021)
Charles A. Ellis, Mohammad S. Eslampanah Sendi, Jon T. Willie, Babak Mahmoudi
Hierarchical Neural Network with Layer-wise Relevance Propagation for Interpretable Multiclass Neural State Classification. NER (2021)
Charles A. Ellis, Mohammad S. Eslampanah Sendi, Sergey M. Plis, Robyn L. Miller, Vince D. Calhoun
Algorithm-Agnostic Explainability for Unsupervised Clustering. CoRR (2021)
Charles A. Ellis, Mohammad S. Eslampanah Sendi, Robyn L. Miller, Vince D. Calhoun
A Novel Activation Maximization-based Approach for Insight into Electrophysiology Classifiers. BIBM (2021)
Charles A. Ellis, Ping Gu, Mohammad S. Eslampanah Sendi, Daniel Huddleston, Ashish Sharma, Babak Mahmoudi
A Cloud-based Framework for Implementing Portable Machine Learning Pipelines for Neural Data Analysis. EMBC (2019)