| Using deep learning to annotate the protein universe ML Bileschi, D Belanger, DH Bryant, T Sanderson, B Carter, D Sculley, ... Nature Biotechnology, 1-6, 2022 | 377 | 2022 |
| Antibody complementarity determining region design using high-capacity machine learning G Liu, H Zeng, J Mueller, B Carter, Z Wang, J Schilz, G Horny, ... Bioinformatics 36 (7), 2126-2133, 2020 | 219 | 2020 |
| Lost in pruning: The effects of pruning neural networks beyond test accuracy L Liebenwein, C Baykal, B Carter, D Gifford, D Rus Proceedings of Machine Learning and Systems 3, 2021 | 120 | 2021 |
| What made you do this? Understanding black-box decisions with sufficient input subsets B Carter, J Mueller, S Jain, D Gifford The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 95 | 2019 |
| Embedding comparator: Visualizing differences in global structure and local neighborhoods via small multiples A Boggust, B Carter, A Satyanarayan Proceedings of the 27th International Conference on Intelligent User …, 2022 | 92 | 2022 |
| Computationally Optimized SARS-CoV-2 MHC Class I and II Vaccine Formulations Predicted to Target Human Haplotype Distributions G Liu, B Carter, T Bricken, S Jain, M Viard, M Carrington, DK Gifford Cell Systems 11 (2), 131-144. e6, 2020 | 88 | 2020 |
| Overinterpretation reveals image classification model pathologies B Carter, S Jain, JW Mueller, D Gifford Advances in Neural Information Processing Systems 34, 2021 | 70 | 2021 |
| Predicted cellular immunity population coverage gaps for SARS-CoV-2 subunit vaccines and their augmentation by compact peptide sets G Liu, B Carter, DK Gifford Cell Systems 12 (1), 102-107. e4, 2021 | 63 | 2021 |
| Machine learning optimization of peptides for presentation by class II MHCs Z Dai, BD Huisman, H Zeng, B Carter, S Jain, ME Birnbaum, DK Gifford Bioinformatics 37 (19), 3160-3167, 2021 | 17 | 2021 |
| A pan-variant mRNA-LNP T cell vaccine protects HLA transgenic mice from mortality after infection with SARS-CoV-2 Beta B Carter, P Huang, G Liu, Y Liang, PJC Lin, BH Peng, LGA McKay, ... Frontiers in Immunology 14, 710, 2023 | 15 | 2023 |
| Maximum n-times Coverage for Vaccine Design G Liu, A Dimitrakakis, B Carter, D Gifford arXiv preprint arXiv:2101.10902, 2021 | 15 | 2021 |
| Critiquing protein family classification models using sufficient input subsets B Carter, M Bileschi, J Smith, T Sanderson, D Bryant, D Belanger, ... Journal of Computational Biology 27 (8), 1219-1231, 2020 | 13 | 2020 |
| Safety and efficacy of ganciclovir ophthalmic gel for treatment of adenovirus keratoconjunctivitis utilizing cell culture and animal models SP Epstein, KB Fernandez, BM Carter, SA Abdou, N Gadaria, PA Asbell Investigative Ophthalmology & Visual Science 53 (14), 6203-6203, 2012 | 4 | 2012 |
| Machine learning model interpretations explain T cell receptor binding B Carter, J Krog, ME Birnbaum, DK Gifford bioRxiv, 2023.08. 15.553228, 2023 | 3 | 2023 |
| Survey of Fully Verifiable Voting Cryptoschemes B Carter, K Leidal, D Neal, Z Neely | 3 | 2016 |
| Preliminary Immunogenicity of a Pan-COVID-19 T Cell Vaccine in HLA-A* 02: 01 Mice B Carter, J Chen, C Kaseke, A Dimitrakakis, GD Gaiha, Q Xu, DK Gifford bioRxiv, 2021.05. 02.442052, 2021 | 2 | 2021 |
| Interpretations of Machine Learning and Their Application to Therapeutic Design BM Carter Massachusetts Institute of Technology, 2023 | 1 | 2023 |
| T-cell receptors that are k-binding have defined sequence features H Park, J Krog, B Carter, PA Balivada, EM Pogue, S Anand, ME Birnbaum, ... Frontiers in Immunology 16, 1621201, 2025 | | 2025 |
| Interpreting black-box models through sufficient input subsets BM Carter Massachusetts Institute of Technology, 2019 | | 2019 |
| Local and global model interpretability via backward selection and clustering B Carter, J Mueller, S Jain, D Gifford | | 2018 |
