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Quantum Theory

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Machine learning builds full-QM precision protein force fields in seconds.

Briefings in bioinformatics
Full-quantum mechanics (QM) calculations are extraordinarily precise but difficult to apply to large systems, such as biomolecules. Motivated by the massive demand for efficient calculations for large systems at the full-QM level and by the significa...

DeepAtomicCharge: a new graph convolutional network-based architecture for accurate prediction of atomic charges.

Briefings in bioinformatics
Atomic charges play a very important role in drug-target recognition. However, computation of atomic charges with high-level quantum mechanics (QM) calculations is very time-consuming. A number of machine learning (ML)-based atomic charge prediction ...

A machine learning based intramolecular potential for a flexible organic molecule.

Faraday discussions
Quantum mechanical predictive modelling in chemistry and biology is often hindered by the long time scales and large system sizes required of the computational model. Here, we employ the kernel regression machine learning technique to construct an an...

Radical scavenging activity of natural antioxidants and drugs: Development of a combined machine learning and quantum chemistry protocol.

The Journal of chemical physics
Many natural substances and drugs are radical scavengers that prevent the oxidative damage to fundamental cell components. This process may occur via different mechanisms, among which, one of the most important, is hydrogen atom transfer. The feasibi...

The importance of imagination (or lack thereof) in artificial, human and quantum decision making.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Enlarging upon experiments and analysis that I did jointly some years ago, in which artificial (symbolic, neural-net and pattern) learning and generalization were compared with that of humans, I will emphasize the role of imagination (or lack thereof...

New fundamental evidence of non-classical structure in the combination of natural concepts.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
We recently performed cognitive experiments on conjunctions and negations of two concepts with the aim of investigating the combination problem of concepts. Our experiments confirmed the deviations (conceptual vagueness, underextension, overextension...

Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space.

The journal of physical chemistry letters
Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and ap...