Interpretable Nonlinear Dynamic Modeling of Neural Trajectories. - Yuan Zhao 004; Il Memming Park (NIPS, 2016)

Variational Latent Gaussian Process for Recovering Single-Trial Dynamics from Population Spike Trains. - Yuan Zhao 004; Il Memming Park (Neural Comput., 2017)

Learning Structured Neural Dynamics From Single Trial Population Recording. - Josue Nassar; Scott W. Linderman; Yuan Zhao 004; Mónica F. Bugallo; Il Memming Park (ACSSC, 2018)

Rescuing neural spike train models from bad MLE. - Diego M. Arribas; Yuan Zhao 004; Il Memming Park (NeurIPS, 2020)

Non-parametric generalized linear model. - Matthew Dowling; Yuan Zhao 004; Il Memming Park (CoRR, 2020)

Variational Online Learning of Neural Dynamics. - Yuan Zhao 004; Il Memming Park (Frontiers Comput. Neurosci., 2020)

Stimulus-choice (mis)alignment in primate area MT. - Yuan Zhao 004; Jacob L. Yates; Aaron J. Levi; Alexander C. Huk; Il Memming Park (PLoS Comput. Biol., 2020)

Real-time variational method for learning neural trajectory and its dynamics. - Matthew Dowling; Yuan Zhao 004; Il Memming Park (ICLR, 2023)

Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains. - Matthew Dowling; Yuan Zhao 004; Il Memming Park (ICML, 2023)

Streaming Variational Monte Carlo. - Yuan Zhao 004; Josue Nassar; Ian D. Jordan; Mónica F. Bugallo; Il Memming Park (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Real-Time Machine Learning Strategies for a New Kind of Neuroscience Experiments. - Ayesha Vermani; Matthew Dowling; Hyungju Jeon; Ian D. Jordan; Josue Nassar; Yves Bernaerts; Yuan Zhao 004; Steven Van Vaerenbergh; Il Memming Park (EUSIPCO, 2024)

eXponential FAmily Dynamical Systems (XFADS): Large-scale nonlinear Gaussian state-space modeling. - Matthew Dowling; Yuan Zhao 004; Memming Park (NeurIPS, 2024)

Large-scale variational Gaussian state-space models. - Matthew Dowling; Yuan Zhao 004; Il Memming Park (CoRR, 2024)