| Deep learning improves antimicrobial peptide recognition D Veltri, U Kamath, A Shehu Bioinformatics 34 (16), 2740-2747, 2018 | 299 | 2018 |
| Deep learning for NLP and speech recognition U Kamath, J Liu, J Whitaker Springer, 2019 | 264 | 2019 |
| Explainable artificial intelligence: An introduction to interpretable machine learning U Kamath, J Liu Springer, 2021 | 65 | 2021 |
| Effective automated feature construction and selection for classification of biological sequences U Kamath, K De Jong, A Shehu PloS one 9 (7), e99982, 2014 | 59 | 2014 |
| Improving recognition of antimicrobial peptides and target selectivity through machine learning and genetic programming D Veltri, U Kamath, A Shehu IEEE/ACM transactions on computational biology and bioinformatics 14 (2 …, 2015 | 57 | 2015 |
| An evolutionary algorithm approach for feature generation from sequence data and its application to DNA splice site prediction U Kamath, J Compton, R Islamaj-Doğan, KA De Jong, A Shehu IEEE/ACM Transactions on Computational Biology and Bioinformatics 9 (5 …, 2012 | 43 | 2012 |
| Convolutional neural networks U Kamath, J Liu, J Whitaker, U Kamath, J Liu, J Whitaker Deep learning for NLP and speech recognition, 263-314, 2019 | 38 | 2019 |
| Systems and methods for rapidly building, managing, and sharing machine learning models C Hughes, T Estes, J Liu, C Brandon, U Kamath US Patent App. 16/613,301, 2020 | 35 | 2020 |
| Boosted mean shift clustering Y Ren, U Kamath, C Domeniconi, G Zhang Machine Learning and Knowledge Discovery in Databases: European Conference …, 2014 | 27 | 2014 |
| SAX-EFG: An evolutionary feature generation framework for time series classification U Kamath, J Lin, K De Jong Proceedings of the 2014 Annual Conference on Genetic and Evolutionary …, 2014 | 16 | 2014 |
| Using evolutionary computation to improve SVM classification U Kamath, A Shehu, K De Jong IEEE Congress on Evolutionary Computation, 1-8, 2010 | 16 | 2010 |
| PsychBERT: a mental health language model for social media mental health behavioral analysis V Vajre, M Naylor, U Kamath, A Shehu 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2021 | 13 | 2021 |
| Transfer learning: Domain adaptation U Kamath, J Liu, J Whitaker, U Kamath, J Liu, J Whitaker Deep learning for NLP and speech recognition, 495-535, 2019 | 12 | 2019 |
| Selecting predictive features for recognition of hypersensitive sites of regulatory genomic sequences with an evolutionary algorithm U Kamath, KA De Jong, A Shehu Proceedings of the 12th annual conference on Genetic and evolutionary …, 2010 | 11 | 2010 |
| Bidirectional encoder representations from transformers (BERT) U Kamath, KL Graham, W Emara Transformers for Machine Learning, 43-70, 2022 | 10 | 2022 |
| Quantifying explainability in nlp and analyzing algorithms for performance-explainability tradeoff M Naylor, C French, S Terker, U Kamath arXiv preprint arXiv:2107.05693, 2021 | 9 | 2021 |
| Parallel boosted clustering Y Ren, U Kamath, C Domeniconi, Z Xu Neurocomputing 351, 87-100, 2019 | 9 | 2019 |
| An analysis of a spatial ea parallel boosting algorithm U Kamath, C Domeniconi, KA De Jong Proceedings of the 15th annual conference on Genetic and evolutionary …, 2013 | 9 | 2013 |
| Feature and kernel evolution for recognition of hypersensitive sites in DNA sequences U Kamath, A Shehu, KA De Jong Bio-Inspired Models of Network, Information, and Computing Systems: 5th …, 2012 | 9 | 2012 |
| Transformers for Machine Learning: A Deep Dive U Kamath, K Graham, W Emara Chapman and Hall/CRC, 2022 | 8 | 2022 |
John Chih LiuIntelluron | PhD, University of PennsylvaniaVerified email at seas.upenn.edu
