3 papers
cs.LG2025
SING: SDE Inference via Natural Gradients
Amber Hu, Henry Smith, Scott Linderman
Latent stochastic differential equation (SDE) models are important tools for the unsupervised discovery of dynamical systems from data, with applications ranging from engineering t…
q-bio.NC2024
Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems
Amber Hu, David Zoltowski, Aditya Nair +3
Understanding how the collective activity of neural populations relates to computation and ultimately behavior is a key goal in neuroscience. To this end, statistical methods which…
stat.ML2021
Spectral Top-Down Recovery of Latent Tree Models
Yariv Aizenbud, Ariel Jaffe, Meng Wang +5
Modeling the distribution of high dimensional data by a latent tree graphical model is a prevalent approach in multiple scientific domains. A common task is to infer the underlying…