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Keegan Hines
Keegan Hines
Georgetown University, University of Texas
Verified email at georgetown.edu
Title
Cited by
Cited by
Year
Counterfactual explanations for machine learning: A review
S Verma, J Dickerson, K Hines
2020 NeurIPS Workshop on ML Retrospectives, 2020
2402020
Towards automated machine learning: Evaluation and comparison of AutoML approaches and tools
A Truong, A Walters, J Goodsitt, K Hines, CB Bruss, R Farivar
2019 IEEE 31st international conference on tools with artificial …, 2019
1412019
Determination of parameter identifiability in nonlinear biophysical models: A Bayesian approach
KE Hines, TR Middendorf, RW Aldrich
Journal of General Physiology 143 (3), 401-416, 2014
1272014
A primer on Bayesian inference for biophysical systems
KE Hines
Biophysical journal 108 (9), 2103-2113, 2015
652015
Inferring subunit stoichiometry from single molecule photobleaching
KE Hines
Journal of General Physiology 141 (6), 737-746, 2013
462013
Analyzing single-molecule time series via nonparametric Bayesian inference
KE Hines, JR Bankston, RW Aldrich
Biophysical journal 108 (3), 540-556, 2015
442015
Deeptrax: Embedding graphs of financial transactions
A Khazane, J Rider, M Serpe, A Gogoglou, K Hines, CB Bruss, R Serpe
2019 18th IEEE International Conference On Machine Learning And Applications …, 2019
372019
Counterfactual explanations for machine learning: A review. arXiv 2020
S Verma, J Dickerson, K Hines
arXiv preprint arXiv:2010.10596, 0
14
Counterfactual explanations for machine learning: Challenges revisited
S Verma, J Dickerson, K Hines
arXiv preprint arXiv:2106.07756, 2021
82021
A Multitask Network for Localization and Recognition of Text in Images
MR Sarshogh, KE Hines
2019 IEEE International Conference on Document Analysis and Recognition, 2019
52019
Neural embeddings of transaction data
C Bruss, K Hines
US Patent 10,789,530, 2020
42020
Systems and methods for text localization and recognition in an image of a document
MR Sarshogh, K Hines
US Patent 10,671,878, 2020
42020
On the interpretability and evaluation of graph representation learning
A Gogoglou, CB Bruss, KE Hines
2019 NeurIPS Workshop on Graph Representation Learning, 2019
42019
Graph embeddings at scale
CB Bruss, A Khazane, J Rider, R Serpe, S Nagrecha, KE Hines
arXiv preprint arXiv:1907.01705, 2019
42019
Anomaly Detection in Cyber Network Data Using a Cyber Language Approach
BD Richardson, BJ Radford, SE Davis, K Hines, D Pekarek
arXiv preprint arXiv:1808.10742, 2018
32018
Amortized generation of sequential algorithmic recourses for black-box models
S Verma, K Hines, JP Dickerson
Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8512-8519, 2022
22022
Amortized Generation of Sequential Counterfactual Explanations for Black-box Models
S Verma, K Hines, JP Dickerson
AAAI 2022, 2021
22021
Method and system for detecting drift in text streams
K Hines, CB Bruss
US Patent 10,579,894, 2020
22020
Equalizing Credit Opportunity in Algorithms: Aligning Algorithmic Fairness Research with US Fair Lending Regulation
IE Kumar, KE Hines, JP Dickerson
Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 357-368, 2022
12022
Credit decisioning based on graph neural networks
MR Sarshogh, C Bruss, K Hines
US Patent 11,238,531, 2022
12022
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