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We present Path Integral Sampler~(PIS), a novel algorithm to draw samples from unnormalized probability density functions.
Stochastic control and nonequilibrium thermodynamical systems
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Asymptotically unbiased estimation of physical observables with neural samplers
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Fourier features let networks learn high frequency functions in low dimensional domains
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