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
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
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
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), 18, 2022
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
Database Systems for Advanced Applications: 19th International Conference …, 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
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
Bayesian classifiers for positive unlabeled learning
J He, Y Zhang, X Li, Y Wang
International Conference on Web-Age Information Management, 81-93, 2011
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
ACS omega 7 (30), 26573-26581, 2022
Levenshtein augmentation improves performance of smiles based deep-learning synthesis prediction
D Sumner, J He, A Thakkar, O Engkvist, EJ Bjerrum
Transformer neural network for structure constrained molecular optimization
J He, F Mattsson, M Forsberg, EJ Bjerrum, O Engkvist, C Tyrchan, ...
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
Exhaustive local chemical space exploration using a transformer model
A Tibo, J He, JP Janet, E Nittinger, O Engkvist
Similarity-based pairing improves efficiency of siamese neural networks for regression tasks and uncertainty quantification
Y Zhang, J Menke, J He, E Nittinger, C Tyrchan, O Koch, H Zhao
Journal of Cheminformatics 15 (1), 75, 2023
Transformer neural network-based molecular optimization using general transformations
J He, E Nittinger, C Tyrchan, W Czechtizky, A Patronov, EJ Bjerrum, ...
Reinvent 4: Modern AI–driven generative molecule design
HH Loeffler, J He, A Tibo, JP Janet, A Voronov, LH Mervin, O Engkvist
Journal of Cheminformatics 16 (1), 1-16, 2024
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
Top 10 journals welcome new entries
R Irwin, S Dimitriadis, J He
Physics World, 13, 2005
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Articles 1–20