Improved Adaptive Importance Sampling Based on Variational Inference. - Matthew Dowling; Josue Nassar; Petar M. Djuric; Mónica F. Bugallo (EUSIPCO, 2018)

Tracking of Objects in a Passive Backscattering Tag-to-Tag Network. - Matthew Dowling; Mónica F. Bugallo; Samir R. Das; Petar M. Djuric (SPAWC, 2018)

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

Hida-Matérn Kernel. - Matthew Dowling; Piotr A. Sokól; Il Memming Park (CoRR, 2021)

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)

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)

Nonlinear multiregion neural dynamics with parametric impulse response communication channels. - Matthew Dowling; Cristina Savin (ICLR, 2025)

Meta-Dynamical State Space Models for Integrative Neural Data Analysis. - Ayesha Vermani; Josue Nassar; Hyungju Jeon; Matthew Dowling; Il Memming Park (ICLR, 2025)