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pro vyhledávání: '"van der Mast, Diego"'
Molecular design requires systematic and broadly applicable methods to extract structure-property relationships. The focus of this study is on learning thermodynamic properties from molecular-liquid simulations. The methodology relies on an atomic re
Externí odkaz:
http://arxiv.org/abs/2302.09909
Autor:
Ambekar, Sameer, Tafuro, Matteo, Ankit, Ankit, van der Mast, Diego, Alence, Mark, Athanasiadis, Christos
With the usage of appropriate inductive biases, Counterfactual Generative Networks (CGNs) can generate novel images from random combinations of shape, texture, and background manifolds. These images can be utilized to train an invariant classifier, a
Externí odkaz:
http://arxiv.org/abs/2208.04226