Murat Sorkun

Doctoral Candidate, Department of Applied Physics, Center for Computational Energy Research

Emailm.c.sorkun@tue.nl

Source: Scopus

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11 Citations
5 Article

Pushing the limits of solubility prediction via quality-oriented data selection
Sorkun, M., Koelman, J. M. V. A. V. & Er, S., 22 Jan 2021, In : iScience. 24, 1, 17 p., 101961.
Research output: Contribution to journal › Article › Academic › peer-review

Open Access
An artificial intelligence-aided virtual screening recipe for two-dimensional materials discovery
Sorkun, M., Astruc, S., Koelman, J. M. V. A. V. & Er, S., 24 Jul 2020, In : npj Computational Materials. 6, 1, 10 p., 106.
Research output: Contribution to journal › Article › Academic › peer-review

Open Access
1 Citation (Scopus)
Time series forecasting on multivariate solar radiation data using deep learning (LSTM)
Sorkun, M., Durmaz İncel, Ö. & Paoli, C., 27 Jan 2020, In : Elektrik, Turkish Journal of Electrical Engineering & Computer Sciences. 28, 1, p. 211-223 13 p.
Research output: Contribution to journal › Article › Academic › peer-review

Open Access
1 Citation (Scopus)
AqSolDB, a curated reference set of aqueous solubility and 2D descriptors for a diverse set of compounds
Sorkun, M., Khetan, A. & Er, S., 8 Aug 2019, In : Scientific Data. 6, 1, 8 p., 143.
Research output: Contribution to journal › Article › Academic › peer-review

Open Access
9 Citations (Scopus)
Fraud Detection on Financial Statements Using Data Mining Techniques
Sorkun, M. & Toraman, T., 2017, In : International Journal of Intelligent Systems and Applications in Engineering. 5, 3
Research output: Contribution to journal › Article › Academic › peer-review

Open Access

V2DB: Virtual 2D Materials Database
Sorkun, M. (Creator), Astruc, S. (Creator), Koelman, J. M. V. A. (. (Creator) & Er, S. (Creator), Harvard Dataverse, 2020
DOI: https://doi.org/10.7910/DVN/SNCZF4
Dataset
AqSolDB: A curated reference set of aqueous solubility and 2D descriptors for a diverse set of compounds
Sorkun, M. (Creator), Khetan, A. (Creator) & Er, S. (Creator), Harvard Dataverse, 2019
DOI: https://doi.org/10.7910/DVN/OVHAW8
Dataset

Pushing the limits of solubility prediction via quality-oriented data selection

An artificial intelligence-aided virtual screening recipe for two-dimensional materials discovery

Time series forecasting on multivariate solar radiation data using deep learning (LSTM)

AqSolDB, a curated reference set of aqueous solubility and 2D descriptors for a diverse set of compounds

Fraud Detection on Financial Statements Using Data Mining Techniques

V2DB: Virtual 2D Materials Database

AqSolDB: A curated reference set of aqueous solubility and 2D descriptors for a diverse set of compounds