Prasad Kawthekar 个人学术档案

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Bharath RamsundarDeep Forest Sciences, DeepChem, previously Computable, previously Stanford在 stanford.edu 的电子邮件经过验证
Bowen LiuAndreessen Horowitz, insitro, Stanford在 cs.stanford.edu 的电子邮件经过验证
Joe GomesUniversity of Iowa在 uiowa.edu 的电子邮件经过验证
Christian KästnerCarnegie Mellon University, School of Computer Science在 cs.cmu.edu 的电子邮件经过验证
Pooyan JamshidiAssistant Professor of Computer Science and Engineering, University of South Carolina, Google在 cse.sc.edu 的电子邮件经过验证
Norbert SiegmundProfessor of Computer Science, Leipzig University在 informatik.uni-leipzig.de 的电子邮件经过验证
Miguel VelezGoogle在 alumni.cmu.edu 的电子邮件经过验证
Kevin TianAssistant Professor, University of Texas at Austin在 cs.utexas.edu 的电子邮件经过验证

Prasad Kawthekar

Stanford CS 2018

在 stanford.edu 的电子邮件经过验证 - 首页


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Retrosynthetic reaction prediction using neural sequence-to-sequence models B Liu, B Ramsundar, P Kawthekar, J Shi, J Gomes, Q Luu Nguyen, S Ho, ... ACS central science 3 (10), 1103-1113, 2017	507	2017
Transfer learning for improving model predictions in highly configurable software P Jamshidi, M Velez, C Kästner, N Siegmund, P Kawthekar 2017 IEEE/ACM 12th International Symposium on Software Engineering for …, 2017	125	2017
Evaluating generative models for text generation P Kawthekar, R Rewari, S Bhooshan URL https://web. stanford. edu/class/archive/cs/cs224n/cs224n 1174, 2017	19	2017
Predicting transcriptional regulatory activities with deep convolutional networks J Paggi, A Lamb, K Tian, I Hsu, PL Cedoz, P Kawthekar BioRxiv, 099879, 2017	6	2017
Sensitivity analysis for building evolving and & adaptive robotic software P Kawthekar, C Kästner Proceedings of the IJCAI Workshop on Autonomous Mobile Service Robots (WSR) 7, 2016	5	2016
Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models, ACS Cent Sci. 3 (2017) 1103–1113 B Liu, B Ramsundar, P Kawthekar, J Shi, J Gomes, QL Nguyen, S Ho, ...	4
DART: Deep learning for ART M Dumonal, Y He, P Kawthekar

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