Neo Christopher Chung

Orcid: 0000-0001-6798-8867

According to our database1, Neo Christopher Chung authored at least 18 papers between 2015 and 2023.

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

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2023
Feature perturbation augmentation for reliable evaluation of importance estimators in neural networks.
Pattern Recognit. Lett., December, 2023

Class-Discriminative Attention Maps for Vision Transformers.
CoRR, 2023

Challenges of Large Language Models for Mental Health Counseling.
CoRR, 2023

Integration of Radiomics and Tumor Biomarkers in Interpretable Machine Learning Models.
CoRR, 2023

Feature Perturbation Augmentation for Reliable Evaluation of Importance Estimators.
CoRR, 2023

Fidelity of Interpretability Methods and Perturbation Artifacts in Neural Networks.
Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

Deep Learning Mental Health Dialogue System.
Proceedings of the IEEE International Conference on Big Data and Smart Computing, 2023

2022
Evaluation of Interpretability Methods and Perturbation Artifacts in Deep Neural Networks.
CoRR, 2022

Evaluation of Importance Estimators in Deep Learning Classifiers for Computed Tomography.
Proceedings of the Explainable and Transparent AI and Multi-Agent Systems, 2022

2021
Human in the Loop for Machine Creativity.
CoRR, 2021

Input Bias in Rectified Gradients and Modified Saliency Maps.
Proceedings of the IEEE International Conference on Big Data and Smart Computing, 2021

2020
Removing Brightness Bias in Rectified Gradients.
CoRR, 2020

Statistical significance of cluster membership for unsupervised evaluation of cell identities.
Bioinform., 2020

2019
Truncated Robust Principal Component Analysis and Noise Reduction for Single Cell RNA Sequencing Data.
J. Comput. Biol., 2019

Jaccard/Tanimoto similarity test and estimation methods for biological presence-absence data.
BMC Bioinform., 2019

Concept Saliency Maps to Visualize Relevant Features in Deep Generative Models.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

2018
Truncated Robust Principal Component Analysis and Noise Reduction for Single Cell RNA-seq Data.
Proceedings of the Bioinformatics Research and Applications - 14th International Symposium, 2018

2015
Statistical significance of variables driving systematic variation in high-dimensional data.
Bioinform., 2015


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