This is the complete documentation for v2.0.0 of the package, released on 2026-05-11. OGRePy is a modern Python package for differential geometry and tensor calculus, designed to be both powerful and ...

This valuable computational study presents a conceptually simple and biologically plausible reinforcement-learning framework for motor learning based on policy-gradient methods. The evidence ...

This study provides a computable, direct, and mathematically rigorous approximation to the differential geometry of class manifolds for high-dimensional data, along with non-linear projections from ...

Cavendish Laboratory, Department of Physics, University of Cambridge, J. J. Thomson Avenue, Cambridge CB3 0HE, U.K. ISIS Neutron and Muon Source, STFC Rutherford Appleton Laboratory, Harwell Science ...

One key ingredient in deep learning is the stochastic gradient descent (SGD) algorithm, which allows neural nets to find generalizable solutions at flat minima of the high-dimensional loss function.

A growing body of work underlines striking similarities between biological neural networks and recurrent, binary neural networks. A relatively smaller body of work, however, addresses the similarities ...

Many cell types can find their ways in the environment following gradients of external signaling molecules either by migrating (chemotaxis) or growing (chemotropism) toward the source of the signal.

Gradient Descent is THE most used learning algorithm in Machine Learning and this post will show you almost everything you need to know about it. What’s the one algorithm that’s used in almost every ...