This Python Code can be used to reproduced the figures of our paper "Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation". Please cite the paper if you use this code for research purposes. It requires the torch, numpy and matplotlib libraries to run. All figures will be generated by running python3 experiments.py device, where device can be a PyTorch device name like cpu or cuda:0. Intermediate results will be saved in order to avoid recomputing them if a plot should be changed.
-
Notifications
You must be signed in to change notification settings - Fork 0
Code for reproducing the plots in our paper "Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation"
License
dholzmueller/sampling_experiments
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
Code for reproducing the plots in our paper "Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation"
Resources
License
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published