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Found 3 papers, 1 papers with code
Equivariant Transformer is all you need
We find that it overcomes poor acceptance rates for linear models and observe the scaling law of the acceptance rate as in the large language models with Transformers.
HMC with Normalizing Flows
We propose using Normalizing Flows as a trainable kernel within the molecular dynamics update of Hamiltonian Monte Carlo (HMC).
Towards reduction of autocorrelation in HMC by machine learning
Our proposing algorithm provides consistent central values of expectation values of the action density and one-point Green's function with ones from the original HMC in both the symmetric phase and broken phase within the statistical error.
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