Research output per year
Research output per year
Personal profile
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Dive into the research topics where Joohyung Lee is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Statistical Relational Extension of Answer Set Programming
Lee, J. & Yang, Z., 2023, Reasoning Web. Causality, Explanations and Declarative Knowledge - 18th International Summer School 2022, Tutorial Lectures. Bertossi, L. & Xiao, G. (eds.). Springer Science and Business Media Deutschland GmbH, p. 132-160 29 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13759 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Scopus citations -
Injecting Logical Constraints into Neural Networks via Straight-Through Estimators
Yang, Z., Lee, J. & Park, C., 2022, In: Proceedings of Machine Learning Research. 162, p. 25096-25122 27 p.Research output: Contribution to journal › Conference article › peer-review
3 Scopus citations -
Action language BC+
Babb, J. & Lee, J., Jun 5 2020, In: Journal of Logic and Computation. 30, 4, p. 899-922 24 p.Research output: Contribution to journal › Article › peer-review
5 Scopus citations -
A simple extension of answer set programs to embrace neural networks (extended abstract)
Yang, Z., Ishay, A. & Lee, J., Sep 19 2020, In: Electronic Proceedings in Theoretical Computer Science, EPTCS. 325Research output: Contribution to journal › Conference article › peer-review
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Elaboration Tolerant Representation of Markov Decision Process via Decision-Theoretic Extension of Probabilistic Action Language +
Wang, Y. I. & Lee, J., 2020, (Accepted/In press) In: Theory and Practice of Logic Programming.Research output: Contribution to journal › Article › peer-review
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RI: Small: Embracing Deep Neural Networks into Probabilistic Answer Set Programming
National Science Foundation (NSF)
10/1/20 → 7/31/24
Project: Research project
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Applications of Combining Neural Networks with Knowledge Representation in Healthcare
4/1/19 → 12/5/19
Project: Research project
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Student Travel Grant for 2018 Principles of Knowledge Representation and Reasoning Conference and Doctoral Consortium
National Science Foundation (NSF)
8/15/18 → 7/31/19
Project: Research project
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RI: Small: Expressive Reasoning and Learning about Actions under Uncertainty via
National Science Foundation (NSF)
8/1/18 → 7/31/22
Project: Research project
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Application of probabilistic logic programming on analysis of electronic health records
4/1/18 → 12/5/18
Project: Research project
Datasets
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Data from: A logic approach to modeling nomenclatural change
Franz, N. (Creator), Zhang, C. (Creator) & Lee, J. (Creator), DRYAD, Jan 31 2018
DOI: 10.5061/dryad.cd13v, https://datadryad.org/stash/dataset/doi:10.5061/dryad.cd13v
Dataset
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Data from: A logic approach to modeling nomenclatural change
Franz, N. (Contributor), Zhang, C. (Contributor) & Lee, J. (Contributor), Zenodo, Jan 31 2018
DOI: 10.5061/dryad.cd13v, https://zenodo.org/record/4964501
Dataset