Sheng-J / SCNTK Public

Efficient Statistical Tests: A Neural Tangent Kernel Approach, ICML2021

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Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
backup_files		backup_files
cifar10_1000		cifar10_1000
cifar10_2000		cifar10_2000
cifar10_last		cifar10_last
mnist_ganmnist_400		mnist_ganmnist_400
mnist_ganmnist_600		mnist_ganmnist_600
nt_cifar10_exact		nt_cifar10_exact
nt_cifar10_exact_nocos		nt_cifar10_exact_nocos
nt_mnist_200_exact		nt_mnist_200_exact
nt_mnist_200_exact_nocos		nt_mnist_200_exact_nocos
nt_mnist_400_exact		nt_mnist_400_exact
nt_mnist_400_exact_nocos		nt_mnist_400_exact_nocos
nt_mnist_400_montecarlo		nt_mnist_400_montecarlo
nt_mnist_600_exact		nt_mnist_600_exact
ntktst_cifar10		ntktst_cifar10
ntktst_cifar10_2		ntktst_cifar10_2
README.md		README.md
flax_ntk.py		flax_ntk.py
main.py		main.py
main_laplace.py		main_laplace.py
mmd_d.py		mmd_d.py
nt_ntk.py		nt_ntk.py
nt_ntk_nocos.py		nt_ntk_nocos.py
run.sh		run.sh
run_cifar10.sh		run_cifar10.sh
run_mnist.sh		run_mnist.sh
run_mnist_3layers.sh		run_mnist_3layers.sh
run_mnist_opt.sh		run_mnist_opt.sh
run_mnist_type1.sh		run_mnist_type1.sh
test.py		test.py