An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)
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Updated
May 20, 2022 - Jupyter Notebook
An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)
Samplers from the paper "Stochastic Gradient MCMC with Repulsive Forces"
Variance reduction in energy estimators accelerates the exponential convergence in deep learning (ICLR'21)
The GitHub repository for "Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics", ICML 2024
Companion code to the publication Baker, Fearnhead, Fox, Nemeth (2018) Control Variates for Stochastic Gradient MCMC. Statistics and Computing. Available from https://link.springer.com/article/10.1007/s11222-018-9826-2.
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