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It combines Graphics Processing Unit (GPU)-accelerated simulations with efficient training of tens of millions of parameters derived from the maximum-entropy principle to determine 3D structures of chromosomes that accurately reproduce Hi-C-like data. FI-Chrom does not make any a priori assumptions regarding chromosome architecture, making it applicable to any chromosome conformation capture experiment. Its derived structural ensembles capture all essential features from the short- and long-range interactions of typical chromosome organization, such as segregated compartments, chromosome territories, and fully or partially formed loops. Although Hi-C contains only structural information, FI-Chrom extends these data by revealing an emergent dynamical mechanism encoded in the inferred energy landscape. For example, simulations show that chromatin loops are not static architectural features but rather transient structural elements. 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