Understanding molecular behaviour allows researchers to predict the physical and chemical properties of complex systems1, such as how a protein folds or how a drug binds to its target. These insights are critical across biology, chemistry, and materials science2, especially when experiments are costly, time-consuming, or difficult to scale. Yet molecular science has long grappled… Read more »
InstaDeep is pleased to announce the formation of a new Quantum Machine Learning (QML) team within the company’s well-established research department. The announcement coincides with the publication of the “Autoregressive neural-network wavefunctions for ab initio quantum chemistry” research paper in the leading science journal, Nature Machine Intelligence. Publication in Nature Machine Intelligence The paper was… Read more »
InstaDeep is delighted to announce that a collaborative research project with a team from the University of Oxford on “Autoregressive neural-network wavefunctions for ab initio quantum chemistry” has been published in Nature Machine Intelligence magazine. The paper was authored by Dr Thomas Barrett of InstaDeep as well as Prof A. I. Lvovsky and Aleksei Malyshev… Read more »