Random Functions as Data Compressors for Machine Learning of Molecular Processes.
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| Title: | Random Functions as Data Compressors for Machine Learning of Molecular Processes. |
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| Authors: | Debnath J; Department of Theoretical Biophysics, Max Planck Institute of Biophysics, 60438 Frankfurt am Main, Germany., Hummer G; Department of Theoretical Biophysics, Max Planck Institute of Biophysics, 60438 Frankfurt am Main, Germany.; Institute of Biophysics, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany. |
| Source: | Journal of chemical theory and computation [J Chem Theory Comput] 2026 Feb 10; Vol. 22 (3), pp. 1504-1513. Date of Electronic Publication: 2026 Jan 29. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: American Chemical Society Country of Publication: United States NLM ID: 101232704 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1549-9626 (Electronic) Linking ISSN: 15499618 NLM ISO Abbreviation: J Chem Theory Comput Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 1549-9626 |
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| DOI: | 10.1021/acs.jctc.5c01638 |
