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neurips_bdl_starter_kit's Introduction

NeurIPS BDL Approximate Inference Competition - Starting Kit

This is a starting kit for the BDL competition.

Please see the competition website for detailed information.

We include 4 ipython notebooks:

We also include the metrics.py code that is used to evaluate the submissions. For development phase datasets we also include the target HMC predictions.

Finally, we include sample submissions for the light track and extended track for submission format reference.

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andrehuang avatar izmailovpavel avatar sanaelotfi avatar sharadmv avatar

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neurips_bdl_starter_kit's Issues

Are the baseline models and HMC sample checkpoint available?

Hi Pavel!

I saw that on the competition website, it says

... we will release several baselines, including stochastic MCMC, variational methods, and deep ensembles.
We will upload HMC samples on other model-dataset pairs over time.

but I can only find the HMC checkpoints on CIFAR-10, 100 with PreResNet-20 at the Colab link.

I am wondering if you can point me to the code base for the baseline methods, and other available HMC checkpoints? Thanks a lot!!

Best,
Tim

HMC CIFAR10 checkpoint sample performance mismatch

Hello Pavel!

I was trying to run the HMC checkpoints provided here, but I noticed that if I simply run the colab notebook with the full CIFAR10 test set, the test accuracy is 0.8247, which doesn't match the test accuracy provided from the ckpt_dict["accuracy"] (i.e., 0.9601807) for the default checkpoint chain 0, sample 152.

To reproduce it, you can simply change the notebook ceil from

num_inputs = 100

x_test, y_test = test_set
input, target = x_test[0, :num_inputs], y_test[0, :num_inputs]

to

x_test, y_test = test_set
input, target = x_test[0], y_test[0]

and run all.

Did I do something wrong? How can I reproduce the accuracy from ckpt_dict["accuracy"] for a give checkpoint?

Thank a lot!!

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