Statistical significance of variables driving systematic variation in high-dimensional data. - Neo Christopher Chung; John D. Storey (Bioinform., 2015)

Truncated Robust Principal Component Analysis and Noise Reduction for Single Cell RNA-seq Data. - Krzysztof Gogolewski; Maciej Sykulski; Neo Christopher Chung; Anna Gambin (ISBRA, 2018)

Concept Saliency Maps to Visualize Relevant Features in Deep Generative Models. - Lennart Brocki; Neo Christopher Chung (ICMLA, 2019)

Jaccard/Tanimoto similarity test and estimation methods for biological presence-absence data. - Neo Christopher Chung; Blazej Miasojedow; Michal Startek; Anna Gambin (BMC Bioinform., 2019)

Truncated Robust Principal Component Analysis and Noise Reduction for Single Cell RNA Sequencing Data. - Krzysztof Gogolewski; Maciej Sykulski; Neo Christopher Chung; Anna Gambin (J. Comput. Biol., 2019)

Statistical significance of cluster membership for unsupervised evaluation of cell identities. - Neo Christopher Chung (Bioinform., 2020)

Removing Brightness Bias in Rectified Gradients. - Lennart Brocki; Neo Christopher Chung (CoRR, 2020)

Input Bias in Rectified Gradients and Modified Saliency Maps. - Lennart Brocki; Neo Christopher Chung (BigComp, 2021)

Human in the Loop for Machine Creativity. - Neo Christopher Chung (CoRR, 2021)

Evaluation of Importance Estimators in Deep Learning Classifiers for Computed Tomography. - Lennart Brocki; Wistan Marchadour; Jonas Maison; Bogdan Badic; Panagiotis G. Papadimitroulas; Mathieu Hatt; Franck Vermet; Neo Christopher Chung (EXTRAAMAS@AAMAS, 2022)

Evaluation of Interpretability Methods and Perturbation Artifacts in Deep Neural Networks. - Lennart Brocki; Neo Christopher Chung (CoRR, 2022)

Deep Learning Mental Health Dialogue System. - Lennart Brocki; George C. Dyer; Anna Gladka; Neo Christopher Chung (BigComp, 2023)

Fidelity of Interpretability Methods and Perturbation Artifacts in Neural Networks. - Lennart Brocki; Neo Christopher Chung (Tiny Papers @ ICLR, 2023)

Feature Perturbation Augmentation for Reliable Evaluation of Importance Estimators. - Lennart Brocki; Neo Christopher Chung (CoRR, 2023)

Integration of Radiomics and Tumor Biomarkers in Interpretable Machine Learning Models. - Lennart Brocki; Neo Christopher Chung (CoRR, 2023)

Challenges of Large Language Models for Mental Health Counseling. - Neo Christopher Chung; George C. Dyer; Lennart Brocki (CoRR, 2023)

Class-Discriminative Attention Maps for Vision Transformers. - Lennart Brocki; Neo Christopher Chung (CoRR, 2023)

Feature perturbation augmentation for reliable evaluation of importance estimators in neural networks. - Lennart Brocki; Neo Christopher Chung (Pattern Recognit. Lett., 2023)

False Sense of Security in Explainable Artificial Intelligence (XAI). - Neo Christopher Chung; Hongkyou Chung; Hearim Lee; Hongbeom Chung; Lennart Brocki; George C. Dyer (CoRR, 2024)

Class-Discriminative Attention Maps for Vision Transformers. - Lennart Brocki; Jakub Binda; Neo Christopher Chung (Trans. Mach. Learn. Res., 2024)