I am presently working on learning weighted ensemble <https://arxiv.org/pdf/1906.00856.pdf> sampling techniques and was curious if any here have worked with them before. The technique seems promising and has enjoyed quite a bit of success (even above MCMC <https://en.wikipedia.org/wiki/Markov_chain_Monte_Carlo>) in circles concerned with reaction rates for rare events.
Some points of interest for me include: 1. A better sampling of fringe-outlier works/art from streaming services. 2. An alternative (bin-based sampling) to globally defined "fitness" measures in evolutionary modeling. 3. An application of diffusion-limited aggregation to general search (especially in the face of limited resources) 4. An application of linear logic to optimization problems in conformation prediction <https://en.wikipedia.org/wiki/Protein_structure_prediction>. 5. Investigation of dynamical properties, such as distribution of trajectories with "high winding number", on strange attractors. While I am just beginning to grok the technique, I thought it might be fruitful to ask here. Jon
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