Nonparametric Estimation via Variance-Reduced Sketching Presented by Daren Wang, University of Notre Dame Thursday, January 25 2024 3:30 PM-4:30 PM ET AUST 105 Webex Meeting Link Coffee will be served at 3:00 pm in the Noether Lounge (AUST 326) Nonparametric models are of great interest in various scientific and engineering disciplines. Classical kernel methods, while […]

Continuous Statistical Models for Modern Computational Neuroscience Presented by William Consagra, Harvard Medical School Monday, January 29 2024 3:30 PM-4:30 PM ET AUST 105 Webex Meeting Link Coffee will be served at 3:00 pm in the Noether Lounge (AUST 326) Recent advances in neuroimaging technologies hold great promise to bolster our understanding of the structure […]

Non-convex Bayesian Learning via Stochastic Gradient MCMC and Schrödinger Bridge Presented by Wei Deng, Morgan Stanley Monday, February 5 2024 3:30 PM-4:30 PM ET AUST 105 Webex Meeting Link Coffee will be served at 3:00 pm in the Noether Lounge (AUST 326) Generating models from data relies on Monte Carlo methods; generating data from models […]

Characterizing Human Reward-based Decision-making Behavior with Reinforcement Learning Models Presented by Xingche Guo, Columbia University Tuesday, February 6 2024 3:30 PM-4:30 PM ET AUST 105 Webex Meeting Link Coffee will be served at 3:00 pm in the Noether Lounge (AUST 326) Major depressive disorder (MDD) is one of the leading causes of disability-adjusted life years. […]

Practicality meets Optimality: Real-Time Statistical Inference under Complex Constraints Presented by Sen Na, University of California, Berkeley Thursday, February 8 2024 3:30 PM-4:30 PM ET AUST 105 Webex Meeting Link Coffee will be served at 3:00 pm in the Noether Lounge (AUST 326) Constrained estimation problems are prevalent in statistics, machine learning, and engineering. These […]

Identifiable and interpretable nonparametric factor analysis Presented by Maoran Xu, Duke University Monday, January 22 2024 3:30 PM-4:30 PM ET AUST 105 Webex Meeting Link Coffee will be served at 3:00 pm in the Noether Lounge (AUST 326) Factor models have been widely used to summarize the variability of high-dimensional data through a set of […]

Modeling Extremal Streamflow using Deep Learning Approximations and a Flexible Spatial Process Presented by Reetam Majumder, North Carolina State University Thursday, January 18 2024 3:30 PM-4:30 PM ET AUST 105 Webex Meeting Link Coffee will be served at 3:00 pm in the Noether Lounge (AUST 326) Quantifying changes in the probability and magnitude of extreme […]

Multi-model Ensemble Analysis with Neural Network Gaussian Processes Presented by Trevor Harris, Texas A&M University, Department of Statistics Tuesday, January 16 2024 3:30 PM-4:30 PM ET AUST 105 Webex Meeting Link Coffee will be served at 3:00 pm in the Noether Lounge (AUST 326) Multi-model ensemble analysis integrates information from multiple climate models into a […]

Some New Developments On Pairwise Likelihood Estimation & Testing In Latent Variable Models Presented by DR. IRINI MOUSTAKI, LONDON SCHOOL OF ECONOMICS Friday, December  1 11:00 a.m. ET Virtual meeting – Webex meeting link Pairwise likelihood is a limited-information method used to estimate latent variable models, including factor analyses of categorical data. It avoids evaluating […]

Joint Collaborative Statistics Colloquium Network analytics with applications to input-output tables Presented by Professor Jun Yan, Department of Statistics, University of Connecticut Thursday, Dec. 7 2023 8:00 PM-9:00 PM ET (Friday, Dec. 8, 9 AM Beijing) AUST 110 Webex Meeting Link Voov Meeting Link (meeting id: 861-447-545) Weighted, directed networks defined by national or multi-regional […]