David A. Kelly

According to our database, David A. Kelly authored at least 21 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

If It's Good Enough for You, It's Good Enough for Me: Transferability of Audio Sufficiencies across Models.

David A. Kelly, Hana Chockler

CoRR, April, 2026

I Guess That's Why They Call it the Blues: Causal Analysis for Audio Classifiers.

David A. Kelly, Hana Chockler

CoRR, January, 2026

Causal Explanations for Image Classifiers.

Hana Chockler, David A. Kelly, Daniel Kroening, Youcheng Sun

J. Artif. Intell. Res., 2026

2025

Out-of-the-box: Black-box Causal Attacks on Object Detectors.

Melane Navaratnarajah, David A. Kelly, Hana Chockler

CoRR, December, 2025

Activation-Deactivation: A General Framework for Robust Post-hoc Explainable AI.

Akchunya Chanchal, David A. Kelly, Hana Chockler

CoRR, October, 2025

Evaluation of Black-Box XAI Approaches for Predictors of Values of Boolean Formulae.

Stav Armoni-Friedmann, Hana Chockler, David A. Kelly

CoRR, September, 2025

Causal Identification of Sufficient, Contrastive and Complete Feature Sets in Image Classification.

David A. Kelly, Hana Chockler

CoRR, July, 2025

SpecReX: Explainable AI for Raman Spectroscopy.

Nathan Blake, David A. Kelly, Akchunya Chanchal, Sarah Kapllani-Mucaj, Geraint Thomas, Hana Chockler

CoRR, March, 2025

3D ReX: Causal Explanations in 3D Neuroimaging Classification.

Melane Navaratnarajah, Sophie A. Martin, David A. Kelly, Nathan Blake, Hana Chockler

CoRR, February, 2025

To BEE or not to BEE: Estimating more than Entropy with Biased Entropy Estimators.

Ilaria Pia La Torre, David A. Kelly, Héctor Menéndez, David Clark

CoRR, January, 2025

Explaining Negative Classifications of AI Models in Tumor Diagnosis.

David A. Kelly, Hana Chockler, Nathan Blake

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

I Am Big, You Are Little; I Am Right, You Are Wrong.

David A. Kelly, Akchunya Chanchal, Nathan Blake

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

MRxaI: Black-Box Explainability for Image Classifiers in a Medical Setting.

Nathan Blake, David A. Kelly, Santiago Calderon Pena, Akchunya Chanchal, Hana Chockler

Proceedings of the Second Workshop on Second Workshop on Explainable Artificial Intelligence for the Medical Domain (EXPLIMED 2025) co-located with 28th European Conference on Artificial Intelligence (ECAI 2025), 2025

Multiple Different Black Box Explanations for Image Classifiers.

Hana Chockler, David A. Kelly, Daniel Kroening

Proceedings of the ECAI 2025 - 28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy, 2025

2024

DiscreteEntropy.jl: Entropy Estimation of Discrete Random Variables with Julia.

David A. Kelly, Ilaria Pia La Torre

J. Open Source Softw., 2024

Real-Time Incremental Explanations for Object Detectors.

Santiago Calderon Pena, Hana Chockler, David A. Kelly

CoRR, 2024

2023

You Only Explain Once.

David A. Kelly, Hana Chockler, Daniel Kroening, Nathan Blake, Aditi Ramaswamy, Melane Navaratnarajah, Aaditya Shivakumar

CoRR, 2023

Multiple Different Explanations for Image Classifiers.

Hana Chockler, David A. Kelly, Daniel Kroening

CoRR, 2023

StableYolo: Optimizing Image Generation for Large Language Models.

Harel Berger, Aidan Dakhama, Zishuo Ding, Karine Even-Mendoza, David A. Kelly, Héctor D. Menéndez, Rebecca Moussa, Federica Sarro

Proceedings of the Search-Based Software Engineering - 15th International Symposium, 2023

June: A Type Testability Transformation for Improved ATG Performance.

Dan Bruce, David A. Kelly, Héctor D. Menéndez, Earl T. Barr, David Clark

Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, 2023

2019

SafeStrings: Representing Strings as Structured Data.

David A. Kelly, Mark Marron, David Clark, Earl T. Barr

CoRR, 2019