15 citations · 23 across the 4 of their papers we have counts for
4 papers
Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains
Matthew Dowling, Yuan Zhao, Il Memming Park
Latent Gaussian process (GP) models are widely used in neuroscience to uncover hidden state evolutions from sequential observations, mainly in neural activity recordings. While lat…
Real-Time Variational Method for Learning Neural Trajectory and its Dynamics
Matthew Dowling, Yuan Zhao, Il Memming Park
Latent variable models have become instrumental in computational neuroscience for reasoning about neural computation. This has fostered the development of powerful offline algorith…
Low-frequency Image Deep Steganography: Manipulate the Frequency Distribution to Hide Secrets with Tenacious Robustness
Huajie Chen, Tianqing Zhu, Yuan Zhao +3
Image deep steganography (IDS) is a technique that utilizes deep learning to embed a secret image invisibly into a cover image to generate a container image. However, the container…
Interpretable Nonlinear Dynamic Modeling of Neural Trajectories
Yuan Zhao, Il Memming Park
A central challenge in neuroscience is understanding how neural system implements computation through its dynamics. We propose a nonlinear time series model aimed at characterizing…