Continuous Delayed-Memory Stochastic Gradient Descent for Continuous-Time Reinforcement Learning from Astrophysical Time Series
ScientificML
Proposes a continuous delayed-memory stochastic gradient descent method combined with neural network-parameterized stochastic differential equations to model quasar brightness variations from astronomical survey time series.
See LICENSE file quasartime seriesstochastic differential equations