Jiazhen He
Cited by
Cited by
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
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
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
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
Molecular optimization by capturing chemist’s intuition using deep neural networks
J He, H You, E Sandström, E Nittinger, EJ Bjerrum, C Tyrchan, ...
Journal of cheminformatics 13 (1), 1-17, 2021
Chemformer: a pre-trained transformer for computational chemistry
R Irwin, S Dimitriadis, J He, EJ Bjerrum
Machine Learning: Science and Technology 3 (1), 015022, 2022
MOOCs meet measurement theory: a topic-modelling approach
J He, BIP Rubinstein, J Bailey, R Zhang, S Milligan, J Chan
Thirtieth AAAI Conference on Artificial Intelligence, 2016
Bayesian classifiers for positive unlabeled learning
J He, Y Zhang, X Li, Y Wang
International Conference on Web-Age Information Management, 81-93, 2011
Levenshtein augmentation improves performance of smiles based deep-learning synthesis prediction
D Sumner, J He, A Thakkar, O Engkvist, EJ Bjerrum
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
Transformer neural network for structure constrained molecular optimization
J He, F Mattsson, M Forsberg, EJ Bjerrum, O Engkvist, C Tyrchan, ...
Transformer-based molecular optimization beyond matched molecular pairs
J He, E Nittinger, C Tyrchan, W Czechtizky, A Patronov, EJ Bjerrum, ...
Journal of cheminformatics 14 (1), 1-14, 2022
Implications of Additivity and Nonadditivity for Machine Learning and Deep Learning Models in Drug Design
K Kwapien, E Nittinger, J He, C Margreitter, A Voronov, C Tyrchan
Transformer Neural Network-Based Molecular Optimization Using General Transformations
J He, E Nittinger, C Tyrchan, W Czechtizky, A Patronov, EJ Bjerrum, ...
Machine Learning for Feedback in Massive Open Online Courses
J He
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
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