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This repo contains code for the paper Approximating the Permanent by Sampling from Adaptive Partitions

Neurips 2019 Figure 2 plots were made with make_fig2_plots.py
Neurips 2019 Figure 3 plots were made with replot_fromPickle_permanent_bound_tightness_VS_n in compare_bounds.py
Neurips 2019 Figure 4 plots were made with plot_log_likelihoods and plot_mean_squared_errors in /Users/jkuck/tracking_research/muti_target_1dSpring/run_experiments.py

Neurips 2019 Table 1 was made with produce_real_world_network_table.py


To sample a permutation from the distribution defined by the permanent call sample_permutation() by running

$ python nestingUB_gumbel_sample_permanent.py

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