| Benchmarking deep learning interpretability in time series predictions AA Ismail, M Gunady, HC Bravo, S Feizi Advances in Neural Information Processing Systems 33, 6441--6452, 2020 | 198 | 2020 |
| Improving deep learning interpretability by saliency guided training AA Ismail, H Corrada Bravo, S Feizi Advances in Neural Information Processing Systems 34, 26726-26739, 2021 | 81 | 2021 |
| The alzheimer's disease prediction of longitudinal evolution (TADPOLE) challenge: Results after 1 year follow-up RV Marinescu, NP Oxtoby, AL Young, EE Bron, AW Toga, MW Weiner, ... arXiv preprint arXiv:2002.03419, 2020 | 58 | 2020 |
| Input-cell attention reduces vanishing saliency of recurrent neural networks AA Ismail, M Gunady, L Pessoa, H Corrada Bravo, S Feizi Advances in Neural Information Processing Systems 32, 2019 | 56 | 2019 |
| Improving long-horizon forecasts with expectation-biased LSTM networks AA Ismail, T Wood, HC Bravo arXiv preprint arXiv:1804.06776, 2018 | 31 | 2018 |
| Improving multimodal accuracy through modality pre-training and attention AA Ismail, M Hasan, F Ishtiaq arXiv preprint arXiv:2011.06102, 2020 | 22 | 2020 |
| Interpretable mixture of experts AA Ismail, SÖ Arik, J Yoon, A Taly, S Feizi, T Pfister arXiv preprint arXiv:2206.02107, 2022 | 10 | 2022 |
| Interpretable mixture of experts for structured data AA Ismail, SÖ Arik, J Yoon, A Taly, S Feizi, T Pfister arXiv preprint arXiv:2206.02107, 2022 | 10 | 2022 |
| Concept bottleneck generative models AA Ismail, J Adebayo, HC Bravo, S Ra, K Cho The Twelfth International Conference on Learning Representations, 2023 | 7 | 2023 |
| Methods and systems for multimodal content analytics MM Hasan, AA Ismail, F Ishtiaq US Patent App. 17/099,292, 2021 | 6 | 2021 |
| Antibody domainbed: Out-of-distribution generalization in therapeutic protein design N Tagasovska, JW Park, M Kirchmeyer, NC Frey, AM Watkins, AA Ismail, ... arXiv preprint arXiv:2407.21028, 2024 | 3 | 2024 |
| The Alzheimer’s disease prediction of longitudinal evolution (TADPOLE) challenge: results after 1 year follow-up RV Marinescu, NP Oxtoby, AL Young, EE Bron, AW Toga, MW Weiner, ... ArXiv Preprint ArXiv, 2002 | 3 | 2002 |
| LIMO: learning programming using interactive map activities RY Tahboub, J Shin, A Abdelsalam, JW Aref, WG Aref, S Prabhakar Proceedings of the 23rd SIGSPATIAL International Conference on Advances in …, 2015 | 2 | 2015 |
| Cramming Protein Language Model Training in 24 GPU Hours NC Frey, T Joren, A Ismail, A Goodman, R Bonneau, K Cho, V Gligorijevic bioRxiv, 2024.05. 14.594108, 2024 | | 2024 |
| Interpretable Deep Learning for Time Series AA Ismail University of Maryland, College Park, 2022 | | 2022 |
| On map-centric programming environments: vision paper WG Aref, S Prabhakar, J Shin, RY Tahboub, A Abdelsalam, JW Aref Proceedings of the 23rd SIGSPATIAL International Conference on Advances in …, 2015 | | 2015 |
| Supplementary Materials: Improving Deep Learning Interpretability by Saliency Guided Training AA Ismail, HC Bravo, S Feizi | | |
| Supplementary Material: Benchmarking Deep Learning Interpretability in Time Series Predictions AA Ismail, M Gunady, HC Bravo, S Feizi | | |
Hector Corrada BravoAssociate Professor of Computer Science, University of MarylandVerified email at umiacs.umd.edu
