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Charles A. Ellis
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2020 – today
- 2024
- [c22]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: 125-128 - [i3]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 abs/2406.13305 (2024) - 2023
- [j2]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) - [c21]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: 255-259 - [c20]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: 2466-2473 - [c19]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: 2474-2481 - [c18]Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
:
A Novel Explainable Fuzzy Clustering Approach for fMRI Dynamic Functional Network Connectivity Analysis. EMBC 2023: 1-4 - [c17]Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
:
A Convolutional Autoencoder-based Explainable Clustering Approach for Resting-State EEG Analysis. EMBC 2023: 1-4 - [c16]Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
:
Neuropsychiatric Disorder Subtyping Via Clustered Deep Learning Classifier Explanations. EMBC 2023: 1-4 - [c15]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: 1-5 - [c14]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: 1-4 - [i2]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 abs/2312.08383 (2023) - 2022
- [j1]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) - [c13]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: 293-296 - [c12]Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
:
An Approach for Estimating Explanation Uncertainty in fMRI dFNC Classification. BIBE 2022: 297-300 - [c11]Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, Vince D. Calhoun
:
Examining Effects of Schizophrenia on EEG with Explainable Deep Learning Models. BIBE 2022: 301-304 - [c10]Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, Vince D. Calhoun
:
Examining Reproducibility of EEG Schizophrenia Biomarkers Across Explainable Machine Learning Models. BIBE 2022: 305-308 - [c9]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: 1643-1646 - [c8]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: 4449-4452 - 2021
- [c7]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: 1-6 - [c6]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: 1-6 - [c5]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: 1-6 - [c4]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: 3358-3365 - [c3]Charles A. Ellis, Rongen Zhang
, Darwin A. Carbajal, Robyn L. Miller, Vince D. Calhoun
, May D. Wang:
Explainable Sleep Stage Classification with Multimodal Electrophysiology Time-series*. EMBC 2021: 2363-2366 - [c2]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: 351-354 - [i1]Charles A. Ellis, Mohammad S. Eslampanah Sendi, Sergey M. Plis, Robyn L. Miller, Vince D. Calhoun
:
Algorithm-Agnostic Explainability for Unsupervised Clustering. CoRR abs/2105.08053 (2021)
2010 – 2019
- 2019
- [c1]Charles A. Ellis, Ping Gu, Mohammad S. Eslampanah Sendi, Daniel E. Huddleston
, Ashish Sharma, Babak Mahmoudi:
A Cloud-based Framework for Implementing Portable Machine Learning Pipelines for Neural Data Analysis. EMBC 2019: 4466-4469
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