| Learning statistical scripts with LSTM recurrent neural networks K Pichotta, R Mooney Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 219 | 2016 |
| Statistical script learning with multi-argument events K Pichotta, R Mooney Proceedings of the 14th Conference of the European Chapter of the …, 2014 | 167 | 2014 |
| Does BERT pretrained on clinical notes reveal sensitive data? E Lehman, S Jain, K Pichotta, Y Goldberg, BC Wallace arXiv preprint arXiv:2104.07762, 2021 | 106 | 2021 |
| Using sentence-level LSTM language models for script inference K Pichotta, RJ Mooney arXiv preprint arXiv:1604.02993, 2016 | 103 | 2016 |
| Statistical script learning with recurrent neural networks K Pichotta, R Mooney Proceedings of the Workshop on Uphill Battles in Language Processing …, 2016 | 23 | 2016 |
| Identifying phrasal verbs using many bilingual corpora K Pichotta, J DeNero Proceedings of the 2013 Conference on Empirical Methods in Natural Language …, 2013 | 15 | 2013 |
| Benchmarking hierarchical script knowledge Y Bisk, J Buys, K Pichotta, Y Choi Proceedings of the 2019 Conference of the North American Chapter of the …, 2019 | 14 | 2019 |
| Better conditional density estimation for neural networks W Tansey, K Pichotta, JG Scott arXiv preprint arXiv:1606.02321, 2016 | 10 | 2016 |
| Semisupervised training of a brain MRI tumor detection model using mined annotations NC Swinburne, V Yadav, J Kim, YR Choi, DC Gutman, JT Yang, N Moss, ... Radiology 303 (1), 80-89, 2022 | 9 | 2022 |
| Relational theories with null values and non-herbrand stable models V Lifschitz, K Pichotta, F Yang Theory and Practice of Logic Programming 12 (4-5), 565-582, 2012 | 3 | 2012 |
| Processing paraphrases and phrasal implicatives in the Bridge questionanswering system K Pichotta Stanford University, Symbolic Systems undergraduate honors thesis, 2008 | 3* | 2008 |
| DNA liquid biopsy-based prediction of cancer-associated venous thromboembolism J Jee, AR Brannon, R Singh, A Derkach, C Fong, A Lee, L Gray, ... Nature Medicine, 1-9, 2024 | 2 | 2024 |
| Advances in statistical script learning K Pichotta | 2 | 2017 |
| DNA Liquid Biopsies for Cancer-Associated Venous Thromboembolism Prediction J Jee, AR Brannon, C Fong, A Lee, L Gray, K Pichotta, A Luthra, ... Blood 142, 569, 2023 | 1 | 2023 |
| Automated annotation for large-scale clinicogenomic models of lung cancer treatment response and overall survival J Jee, C Fong, K Pichotta, T Tran, A Luthra, M Altoe, S Maron, R Shen, ... Cancer Research 83 (7_Supplement), 5721-5721, 2023 | 1 | 2023 |
| AI-assisted clinical data curation to determine genomic biomarkers of cancer metastasis A Luthra, K Pichotta, B Mastrogiacomo, S McCarthy, S Maron, J Gao, ... Cancer Research 82 (12_Supplement), 1158-1158, 2022 | 1 | 2022 |
| Deep nonparametric estimation of discrete conditional distributions via smoothed dyadic partitioning W Tansey, K Pichotta, JG Scott arXiv preprint arXiv:1702.07398, 2017 | 1 | 2017 |
| Statistical Script Learning with Recurrent Neural Nets K Pichotta | 1 | 2015 |
| Combined impact of primary tumor molecular profile and location in the relapse pattern of early-stage, microsatellite stable colorectal cancer. P Manca, A Kris, HS Walch, C Fong, J Jee, K Pichotta, N Schultz, ... Journal of Clinical Oncology 42 (16_suppl), 3603-3603, 2024 | | 2024 |
| Shareable artificial intelligence to extract cancer outcomes from electronic health records. KL Kehl, J Jee, K Pichotta, P Trukhanov, C Fong, M Waters, C Nichols, ... Journal of Clinical Oncology 42 (16_suppl), 11000-11000, 2024 | | 2024 |
