Jiazhen He
Title
Cited by
Cited by
Year
Identifying at-risk students in massive open online courses
J He, J Bailey, B Rubinstein, R Zhang
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
1492015
Naive bayes classifier for positive unlabeled learning with uncertainty
J He, Y Zhang, X Li, Y Wang
Proceedings of the 2010 SIAM international conference on data mining, 361-372, 2010
282010
Learning naive Bayes classifiers from positive and unlabelled examples with uncertainty
J He, Y Zhang, X Li, P Shi
International journal of systems science 43 (10), 1805-1825, 2012
222012
Exploiting transitive similarity and temporal dynamics for similarity search in heterogeneous information networks
J He, J Bailey, R Zhang
International Conference on Database Systems for Advanced Applications, 141-155, 2014
192014
Bayesian classifiers for positive unlabeled learning
J He, Y Zhang, X Li, Y Wang
International Conference on Web-Age Information Management, 81-93, 2011
122011
MOOCs meet measurement theory: a topic-modelling approach
J He, B Rubinstein, J Bailey, R Zhang, S Milligan, J Chan
Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016
102016
Validity: a framework for cross-disciplinary collaboration in mining indicators of learning from MOOC forums
S Milligan, J He, J Bailey, R Zhang, BIP Rubinstein
proceedings of the sixth international conference on learning analytics …, 2016
32016
Molecular Optimization by Capturing Chemist's Intuition Using Deep Neural Networks
J He, H You, E Sandström, E Nittinger, E Bjerrum, C Tyrchan, ...
12020
Levenshtein Augmentation Improves Performance of SMILES Based Deep-Learning Synthesis Prediction
D Sumner, J He, A Thakkar, O Engkvist, EJ Bjerrum
ChemRxiv, 2020
2020
TopicResponse: A Marriage of Topic Modelling and Rasch Modelling for Automatic Measurement in MOOCs
J He, BIP Rubinstein, J Bailey, R Zhang, S Milligan
arXiv preprint arXiv:1607.08720, 2016
2016
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Articles 1–10