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Found 3 papers, 1 papers with code
Multimodal Learning for Materials
Artificial intelligence is transforming computational materials science, improving the prediction of material properties, and accelerating the discovery of novel materials.
Orthogonal Rational Approximation of Transfer Functions for High-Frequency Circuits
The unknown denominator polynomial of the model results in a non-linear problem, which can be replaced with successive solutions of linearized problems following the Sanathanan-Koerner (SK) iteration.
Topogivity: A Machine-Learned Chemical Rule for Discovering Topological Materials
Topological materials present unconventional electronic properties that make them attractive for both basic science and next-generation technological applications.
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