Oct 30, 2023 · Abstract:We develop a theory of flows in the space of Riemannian metrics induced by neural network gradient descent.
We develop a general theory of flows in the space of Riemannian metrics induced by neural network (NN) gradient descent. This is motivated in part by recent ...
Oct 23, 2024 · We develop a general theory of flows in the space of Riemannian metrics induced by neural network (NN) gradient descent.
Oct 30, 2023 · We develop a general theory of flows in the space of Riemannian metrics induced by neural network gradient descent.
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Oct 12, 2024 · We develop a general theory of flows in the space of Riemannian metrics induced by neural network gradient descent.
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Feb 25, 2024 · Deep neural networks work under the manifold hypothesis, that is, that the training data lie on a lower-dimensional manifold.
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Oct 21, 2024 · Overview. The paper develops a general theory of how neural network gradient descent induces flows in the space of Riemannian metrics.
Duration: 40:53
Posted: Mar 16, 2023
Posted: Mar 16, 2023