Suppose I have a custom probability density function defined up to some constant. For example, it can come from a Gibbs distribution with some manually defined potential.
def unnormalized_pdf(x): return torch.exp(-x**2)
Can I use HMC to sample from this distribution? The whole point is not to define the distribution via sampling and conditioning, but define it analytically.