1 citations · 1 across the 4 of their papers we have counts for
5 papers
Stochastic Gradient Descent over P2
Maria Oprea, Qin Li, Yunan Yang
Stochastic gradient descent (SGD) admits diffusion approximations that replace the complicated randomness of stochastic gradients by Gaussian noise, providing a powerful tool for u…
Inverse Problems Over Probability Measure Space
Qin Li, Maria Oprea, Li Wang +1
Define a forward problem as , where the probability distribution is mapped to another distribution using the forward operator . In this work, we inves…
The Distributional Koopman Operator for Random Dynamical Systems
Maria Oprea, Alex Townsend, Yunan Yang
The Distributional Koopman Operator (DKO) is introduced as a way to perform Koopman analysis on random dynamical systems where only aggregate distribution data is available, thereb…
Stochastic Inverse Problem: stability, regularization and Wasserstein gradient flow
Qin Li, Maria Oprea, Li Wang +1
Inverse problems in physical or biological sciences often involve recovering an unknown parameter that is random. The sought-after quantity is a probability distribution of the unk…
Measure-Theoretic Time-Delay Embedding
Jonah Botvinick-Greenhouse, Maria Oprea, Romit Maulik +1
The celebrated Takens' embedding theorem provides a theoretical foundation for reconstructing the full state of a dynamical system from partial observations. However, the classical…