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Machine learning (ML) is increasingly becoming a common tool in computationalchemistry. At the same time, the rapid development of ML methods requires aflexible software framework for designing custom workflows. MLatom 3 is aprogram package designed to leverage the power of ML to enhance typicalcomputational chemistry simulations and to create complex workflows. Thisopen-source package provides plenty of choice to the users who can runsimulations with the command line options, input files, or with scripts usingMLatom as a Python package, both on their computers and on the online XACScloud computing at XACScloud.com. Computational chemists can calculate energiesand thermochemical properties, optimize geometries, run molecular and quantumdynamics, and simulate (ro)vibrational, one-photon UV/vis absorption, andtwo-photon absorption spectra with ML, quantum mechanical, and combined models.The users can choose from an extensive library of methods containingpre-trained ML models and quantum mechanical approximations such as AIQM1approaching coupled-cluster accuracy. The developers can build their own modelsusing various ML algorithms. The great flexibility of MLatom is largely due tothe extensive use of the interfaces to many state-of-the-art software packagesand libraries.

MLatom 3: Platform for machine learning-enhanced computational chemistry simulations and workflows