Learning statistical scripts with LSTM recurrent neural networks K Pichotta, R Mooney Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 223 | 2016 |
Statistical script learning with multi-argument events K Pichotta, R Mooney Proceedings of the 14th Conference of the European Chapter of the …, 2014 | 172 | 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 | 119 | 2021 |
Using sentence-level LSTM language models for script inference K Pichotta, RJ Mooney arXiv preprint arXiv:1604.02993, 2016 | 105 | 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 |
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 | 15 | 2019 |
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 |
Automated real-world data integration improves cancer outcome prediction J Jee, C Fong, K Pichotta, TN Tran, A Luthra, M Waters, C Fu, M Altoe, ... Nature, 1-9, 2024 | 11 | 2024 |
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 | 11 | 2022 |
Better conditional density estimation for neural networks W Tansey, K Pichotta, JG Scott arXiv preprint arXiv:1606.02321, 2016 | 10 | 2016 |
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 30 (9), 2499-2507, 2024 | 6 | 2024 |
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 |
Shareable artificial intelligence to extract cancer outcomes from electronic health records for precision oncology research KL Kehl, J Jee, K Pichotta, MA Paul, P Trukhanov, C Fong, M Waters, ... Nature Communications 15 (1), 9787, 2024 | 2 | 2024 |
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 | 2 | 2023 |
Advances in statistical script learning K Pichotta | 2 | 2017 |
Systematic generation of a clinicogenomic harmonized oncologic real-world dataset (MSK-CHORD) CJ Fong, K Pichotta, T Tran, M Waters, T Fu, M Pirun, M Altoe, ... Cancer Research 84 (6_Supplement), 3892-3892, 2024 | 1 | 2024 |
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 |
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 |
Leaf-smoothed hierarchical softmax for ordinal prediction W Tansey, K Pichotta, J Scott Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 1 | 2018 |