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> the NAIL team incorporated Hamiltonian structure into neural networks ML non-expert here. Is this the same as having an extra column of your input data that'
by awinter-py 6y ago
> the NAIL team incorporated Hamiltonian structure into neural networks
ML non-expert here. Is this the same as having an extra column of your input data that's a hamiltonian of the raw input? Or a kind of neuron that can compute a hamiltonian on an observation? Or something more complicated.
is this like a specialized 'functional region' in a biological brain? (broca's area, cerebellum)
- vutekst 6y agoAlso ML non-expert here. I think this is about a different kind of neuron(your 2nd suggestion). The paper another commenter linked says: Hamiltonian neural network (HNN) intakes position and momenta {q,p}, outputs the scalar function H, takes its gradient to find its position and momentum rates of change, and minimizes the loss <latex equation for a modified loss function that differs from traditional NN> which enforces Hamilton's equations of motion. https://journals.aps.org/pre/abstract/10.1103/PhysRevE.101.062207#fulltext https://journals.aps.org/pre/abstract/10.1103/PhysRevE.101.0...
- zone411 6y agoI haven't used HNNs in practice but it seems that the main difference from common NNs is that the loss function incorporates gradients. It's not a new type of a neuron.