Journal of chemical information and computer sciences.
By A. W., W. A. Wan. 1995
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Anubhav Jain
- Shyue Ping Ong
- Gerbrand Ceder
- Geoffroy Hautier
- Barry Bradlyn
- W. Richards
- Kristin A. Persson
- O. V. Lilienfeld
Citations in the corpus
- Machine Learning Energies of 2 Million Elpasolite (ABC_{2}D_{6}) Crystals. (2015, background): “3General Chemistry, Free University of Brussels, Pleinlaan 2, 1050 Brussels, Belgium (Dated: July 28, 2016) Elpasolite is the predominant quaternary crystal structure (AlNaK2F6 prototype) reported in the Inorganic Crystal Structure Database.”
- Topological materials discovery from crystal symmetry (2021, methodology): “Utilizing the resources of the ICSD [13, 14] and the Materials Project [363], researchers applied the theories of TQC [39, 40, 96, 117–119] and SIs [150, 152, 154, 155] to the automated output of thousands of first-principles investigations of nonmagnetic chemical compounds, resulting in massive dat”
- Optimal Design of Experiments by Combining Coarse and Fine Measurements. (2017, methodology): “We use a standard dataset of the solubility of 1144 organic molecules [27], and describe the molecule by concatenating the Avalon Fingerprint [28], the MACCS Fingerprint [29], and the 1024-bit Morgan6 Fingerprint [24].”
- Graph kernels for chemical informatics (2005, unknown): “The corresponding F kernel is given by: k t d (u, v) = 2k d (u, v) k d (u, u) + k d (v, v) (10) The F similarity is also a special case of the more general Tversky similarity [Tversky, 1977, Rouvray, 1992] defined by: k t d (u, v) = 2k d (u, v) αk d (u, u) + βk d (v, v) (11)”
- Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks (2020, methodology): “Data Augmentation Data augmentation is an important technique that enhances the training set of a network and is used mainly when the training dataset contains only a few samples [16].”
- Crystal structure representations for machine learning models of formation energies (2015, result): “Since the MP database is derived from the ICSD [40, 41], the distribution of elements in the extracted systems roughly match their occurrence in published materials in the literature.”
- Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis (2012, background): “The structure of Li4SnS4 itself is currently not reported in the Inorganic Crystal Database (ICSD) [34] or the Materials Project.”