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ORCIDJiazhen He
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2020 – today
- 2024
[j6]Jiazhen He, Alessandro Tibo, Jon Paul Janet, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Ola Engkvist:
Evaluation of reinforcement learning in transformer-based molecular design. J. Cheminformatics 16(1): 95 (2024)- [i3]Gökçe Geylan, Jon Paul Janet, Alessandro Tibo, Jiazhen He, Atanas Patronov, Mikhail Kabeshov, Florian David, Werngard Czechtizky, Ola Engkvist, Leonardo De Maria:
PepINVENT: Generative peptide design beyond the natural amino acids. CoRR abs/2409.14040 (2024) - 2023
- [j5]Yumeng Zhang, Janosch Menke
, Jiazhen He, Eva Nittinger, Christian Tyrchan, Oliver Koch, Hongtao Zhao:
Similarity-based pairing improves efficiency of siamese neural networks for regression tasks and uncertainty quantification. J. Cheminformatics 15(1): 75 (2023) - 2022
- [j4]Jiazhen He, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Atanas Patronov, Esben Jannik Bjerrum, Ola Engkvist:
Transformer-based molecular optimization beyond matched molecular pairs. J. Cheminformatics 14(1): 18 (2022) - [j3]Ross Irwin, Spyridon Dimitriadis, Jiazhen He, Esben Jannik Bjerrum:
Chemformer: a pre-trained transformer for computational chemistry. Mach. Learn. Sci. Technol. 3(1): 15022 (2022) - 2021
- [j2]Jiazhen He, Huifang You, Emil Sandström, Eva Nittinger, Esben Jannik Bjerrum, Christian Tyrchan, Werngard Czechtizky, Ola Engkvist:
Molecular optimization by capturing chemist's intuition using deep neural networks. J. Cheminformatics 13(1): 26 (2021) - [c7]Zhan Wang, SongPo Tian, Xin Fu, Jiazhen He:
An Effective Image Enhancement Method for Color Fundus Images. ACAI 2021: 43:1-43:5
2010 – 2019
- 2016
- [c6]Jiazhen He, Benjamin I. P. Rubinstein, James Bailey, Rui Zhang, Sandra Milligan, Jeffrey Chan:
MOOCs Meet Measurement Theory: A Topic-Modelling Approach. AAAI 2016: 1195-1201 - [c5]Sandra Milligan, Jiazhen He, James Bailey, Rui Zhang, Benjamin I. P. Rubinstein:
Validity: a framework for cross-disciplinary collaboration in mining indicators of learning from MOOC forums. LAK 2016: 546-547 - [i2]Jiazhen He, Rui Zhang, James Bailey, Benjamin I. P. Rubinstein, Sandra Milligan:
TopicResponse: A Marriage of Topic Modelling and Rasch Modelling for Automatic Measurement in MOOCs. CoRR abs/1607.08720 (2016) - 2015
- [c4]Jiazhen He, James Bailey, Benjamin I. P. Rubinstein, Rui Zhang:
Identifying At-Risk Students in Massive Open Online Courses. AAAI 2015: 1749-1755 - [i1]Jiazhen He, Benjamin I. P. Rubinstein, James Bailey, Rui Zhang, Sandra Milligan, Jeffrey Chan:
MOOCs Meet Measurement Theory: A Topic-Modelling Approach. CoRR abs/1511.07961 (2015) - 2014
- [c3]Jiazhen He, James Bailey, Rui Zhang:
Exploiting Transitive Similarity and Temporal Dynamics for Similarity Search in Heterogeneous Information Networks. DASFAA (2) 2014: 141-155 - 2012
- [j1]Jiazhen He, Yang Zhang, Xue Li, Peng Shi:
Learning naive Bayes classifiers from positive and unlabelled examples with uncertainty. Int. J. Syst. Sci. 43(10): 1805-1825 (2012) - 2011
- [c2]Jiazhen He, Yang Zhang, Xue Li, Yong Wang:
Bayesian Classifiers for Positive Unlabeled Learning. WAIM 2011: 81-93 - 2010
- [c1]Jiazhen He, Yang Zhang, Xue Li, Yong Wang:
Naive Bayes Classifier for Positive Unlabeled Learning with Uncertainty. SDM 2010: 361-372
Coauthor Index
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