The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural Networks (DNNs), Neural ODEs, and Symplectic Neural Networks (SympNets) used with state-of-the-art sampling schemes like Hamiltonian Monte Carlo (HMC) and the No-U-Turn-Sampler (NUTS).
neural-networks bayesian-inference hamiltonian-monte-carlo sampling-methods langevin-dynamics no-u-turn-sampler physics-informed-neural-networks
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Updated
Jan 14, 2023 - Python