Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2024; 33rd International C Michael Wand,Kristína Malinovská,Igor V. Tetko Conferenc

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Elucidation of Molecular Substructures from Nuclear Magnetic Resonance Spectra Using Gradient Boostierse problem. Typically, the QSAR process uses the molecule structure features to produce a predictive model for the molecular activity. In case of the inverse problem, features derived from the molecular activity are used to produce a predictive model for the molecular structure. This work demonstr

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Neural SHAKE: Geometric Constraints in Graph Generative Modelshe number of degrees of freedom. Incorporating prior information about geometric patterns, such as distances, angles, and dihedrals, is crucial for ensuring the accurate physical characteristics of molecules by increasing the likelihood of sampling low-energy conformations. These geometric patterns

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Scaffold Splits Overestimate Virtual Screening Performancey. Data splitting is crucial for better benchmarking of such AI models. Traditional random data splits produce similar molecules between training and test sets, conflicting with the reality of VS libraries which mostly contain structurally distinct compounds. Scaffold split, grouping molecules by sh

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Oscillation-Driven Reservoir Computing for Long-Term Replication of Chaotic Time Seriesus chaotic dynamical systems. However, the prediction horizon is limited owing to the instability of the reservoir-computing system. In this study, to suppress this instability, oscillations were fed into the reservoir network, which exhibited chaotic behavior. In response to oscillations, the reser