our solutions are based on a deeper understanding of complex systems
Hybrid deep generative frameworks for on-demand generation of highly realistic synthetic data in different domains (e.g. financial and physiological time series, biomedical and other images as well as misc unstructured data) that can be used to drastically improve training, testing and proper selection of domain-specific models and indicators
Pre-initialized meta-learning models that can be used for fast few-shot training of the domain-specific models in the cases of sever data limitation
Hybrid approaches, based on combination of multi-complexity measures and computational topology, for the discovery of quantitative and other formalized representations for hard-to-quantify properties and unstructured data
Deep Mantic solutions can be adopted in financial, biomedical, business intelligence and robotics applications
