Jiazhen He

17 papers A* 2A 2Journal 10Unranked 3
YearRankTypeTitle / Venue / Authors
2024 J jnl
Evaluation of reinforcement learning in transformer-based molecular design.
J. Cheminformatics
Jiazhen He, Alessandro Tibo, Jon Paul Janet, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Ola Engkvist
2024 J jnl
PepINVENT: Generative peptide design beyond the natural amino acids.
CoRR
Gökçe Geylan, Jon Paul Janet, Alessandro Tibo, Jiazhen He, Atanas Patronov, Mikhail Kabeshov, Florian David, Werngard Czechtizky, Ola Engkvist, Leonardo De Maria
2024 J jnl
Reinvent 4: Modern AI-driven generative molecule design.
J. Cheminformatics
Hannes H. Loeffler, Jiazhen He, Alessandro Tibo, Jon Paul Janet, Alexey Voronov, Lewis H. Mervin, Ola Engkvist
2023 J jnl
Similarity-based pairing improves efficiency of siamese neural networks for regression tasks and uncertainty quantification.
J. Cheminformatics
Yumeng Zhang, Janosch Menke, Jiazhen He, Eva Nittinger, Christian Tyrchan, Oliver Koch, Hongtao Zhao
2022 J jnl
Chemformer: a pre-trained transformer for computational chemistry.
Mach. Learn. Sci. Technol.
Ross Irwin, Spyridon Dimitriadis, Jiazhen He, Esben Jannik Bjerrum
2022 J jnl
Transformer-based molecular optimization beyond matched molecular pairs.
J. Cheminformatics
Jiazhen He, Eva Nittinger, Christian Tyrchan, Werngard Czechtizky, Atanas Patronov, Esben Jannik Bjerrum, Ola Engkvist
2021 — conf
An Effective Image Enhancement Method for Color Fundus Images.
ACAI
Zhan Wang, SongPo Tian, Xin Fu, Jiazhen He
2021 J jnl
Molecular optimization by capturing chemist's intuition using deep neural networks.
J. Cheminformatics
Jiazhen He, Huifang You, Emil Sandström, Eva Nittinger, Esben Jannik Bjerrum, Christian Tyrchan, Werngard Czechtizky, Ola Engkvist
2016 A* conf
MOOCs Meet Measurement Theory: A Topic-Modelling Approach.
AAAI
Jiazhen He, Benjamin I. P. Rubinstein, James Bailey, Rui Zhang, Sandra Milligan, Jeffrey Chan
2016 J jnl
TopicResponse: A Marriage of Topic Modelling and Rasch Modelling for Automatic Measurement in MOOCs.
CoRR
Jiazhen He, Rui Zhang, James Bailey, Benjamin I. P. Rubinstein, Sandra Milligan
2016 A conf
Validity: a framework for cross-disciplinary collaboration in mining indicators of learning from MOOC forums.
LAK
Sandra Milligan, Jiazhen He, James Bailey, Rui Zhang, Benjamin I. P. Rubinstein
2015 A* conf
Identifying At-Risk Students in Massive Open Online Courses.
AAAI
Jiazhen He, James Bailey, Benjamin I. P. Rubinstein, Rui Zhang
2015 J jnl
MOOCs Meet Measurement Theory: A Topic-Modelling Approach.
CoRR
Jiazhen He, Benjamin I. P. Rubinstein, James Bailey, Rui Zhang, Sandra Milligan, Jeffrey Chan
2014 — conf
Exploiting Transitive Similarity and Temporal Dynamics for Similarity Search in Heterogeneous Information Networks.
DASFAA (2)
Jiazhen He, James Bailey, Rui Zhang
2012 J jnl
Learning naive Bayes classifiers from positive and unlabelled examples with uncertainty.
Int. J. Syst. Sci.
Jiazhen He, Yang Zhang, Xue Li, Peng Shi
2011 — conf
Bayesian Classifiers for Positive Unlabeled Learning.
WAIM
Jiazhen He, Yang Zhang, Xue Li, Yong Wang
2010 A conf
Naive Bayes Classifier for Positive Unlabeled Learning with Uncertainty.
SDM
Jiazhen He, Yang Zhang, Xue Li, Yong Wang