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cs.LG2022
Holographic-(V)AE: an end-to-end SO(3)-Equivariant (Variational) Autoencoder in Fourier Space
Gian Marco Visani, Michael N. Pun, Arman Angaji +1
Group-equivariant neural networks have emerged as a data-efficient approach to solve classification and regression tasks, while respecting the relevant symmetries of the data. Howe…
cs.LG2021
MINIMALIST: Mutual INformatIon Maximization for Amortized Likelihood Inference from Sampled Trajectories
Giulio Isacchini, Natanael Spisak, Armita Nourmohammad +2
Simulation-based inference enables learning the parameters of a model even when its likelihood cannot be computed in practice. One class of methods uses data simulated with differe…