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stat.ML2024★ 2 cited
A Structure-Preserving Kernel Method for Learning Hamiltonian Systems
Jianyu Hu, Juan-Pablo Ortega, Daiying Yin
A structure-preserving kernel ridge regression method is presented that allows the recovery of nonlinear Hamiltonian functions out of datasets made of noisy observations of Hamilto…
stat.ML2023
Learning multi-modal generative models with permutation-invariant encoders and tighter variational objectives
Marcel Hirt, Domenico Campolo, Victoria Leong +1
Devising deep latent variable models for multi-modal data has been a long-standing theme in machine learning research. Multi-modal Variational Autoencoders (VAEs) have been a popul…