Browsing Physics (Scholarly Publications) by Subject "Deep learning"
Now showing items 1-4 of 4
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Data-driven enhancement of cubic phase stability in mixed-cation perovskites
(2021)Mixing cations has been a successful strategy in perovskite synthesis by solution-processing, delivering improvements in the thermodynamic stability as well as in the lattice parameter control. Unfortunately, the relation ... -
Data-driven time propagation of quantum systems with neural networks
(2022)We investigate the potential of supervised machine learning to propagate a quantum system in time. While Markovian dynamics can be learned easily, given a sufficient amount of data, non-Markovian systems are nontrivial and ... -
Data-driven time propagation of quantum systems with neural networks
(2022)We investigate the potential of supervised machine learning to propagate a quantum system in time. While Markovian dynamics can be learned easily, given a sufficient amount of data, non-Markovian systems are nontrivial and ... -
Using Weakly Supervised Deep Learning to Classify and Segment Single-Molecule Break-Junction Conductance Traces
(2021)In order to design molecular electronic devices with high performance and stability, it is crucial to understand their structure-to-property relationships. Single-molecule break junction measurements yield a large number ...