Group meetings are for students and faculty at CMU and UPitt.
The STAMPS webinars are open to everyone.
Following University directives, meetings will transition to virtual presentation from March 20 going forward, from 1:30PM - 2:30PM EST as usual.
January 24 - Shamindra Shrotriya (CMU, Department of Statistics & Data Science) #
Predictive Inference of a Wildfire Risk Pipeline in the United States Proposal Track
January 31 - Troy Raen (University of Pittsburgh, Department of Physics and Astronomy) #
A Bayesian Belief Network for Streaming Classification of the Variable Night Sky (Part 1)
February 7 - Troy Raen (University of Pittsburgh, Department of Physics and Astronomy) #
A Bayesian Belief Network for Streaming Classification of the Variable Night Sky (Part 2)
February 14 - Michael Stanley (CMU, Department of Statistics & Data Science) #
Improving Upon the Bayesian Estimation of Carbon Fluxes (Part 1)
February 28 - Michael Stanley (CMU, Department of Statistics & Data Science) #
Improving Upon the Bayesian Estimation of Carbon Fluxes (Part 2)
March 20 - Samuel Fletcher (University of Minnesota) #
Severity and its potential applications in particle physics data analysis
April 3 - Biprateep Dey (University of Pittsburgh, Department of Physics and Astronomy) #
Using Capsule Networks to find galaxy redshifts from images
Overview: We will discuss methods to infer redshifts of galaxies from images using a combination of Capsule networks and Random Forest Regression.
April 10 - Vikesh Siddhu (CMU, Pittsburgh Quantum Institute) #
(Non)-Convex Optimization in Quantum Information
April 24 - Aaditya Ramdas (CMU, Department of Statistics & Data Science) #
Applications of sequential testing in particle physics
May 1 - Hamish Gordon (CMU, Engineering Research Accelerator and the Center for Atmospheric Particle Studies) #
Clouds and aerosols in weather and climate prediction
May 8 - Nic Dalmasso (CMU, Department of Statistics & Data Science) #
Conditional Density Estimation Tools in Python and R with Applications to Photometric Redshifts and Likelihood-Free Cosmological Inference
May 15 - Lorenzo Tomaselli (CMU, Department of Statistics & Data Science) #
Chemical Fingerprinting of Smoke from Western US Wildfires
May 22 - Liz Wayne (CMU, Department of Biomedical Engineering and Chemical Engineering) #
Understanding macrophage phenotype heterogeneity and its implications in disease
June 12 - Ann Lee (CMU, Department of Statistics & Data Science) #
A Geometry-Based Metric for Mixture Distributions
June 19 - Xiaoyi (Ivy) Gu (CMU, Department of Statistics & Data Science) #
Computationally efficient density estimation via tree-based adaptive histograms and its applications
July 10 - Public Webinar: Adam Sykulski (Department of Mathematics and Statistics, Lancaster University) #
July 24 - Boyan Duan (CMU, Department of Statistics & Data Science) #
Introduction to interactive testing
Aug 7 - Guanglu Zhang (CMU, Department of Mechanical Engineering) #
A Solution Interval Method for Least Squares Parameter Estimation in Nonlinear Models
Aug 14 - Public Webinar: Tommaso Dorigo (INFN-Padova) #
Aug 21 - Parker Holzer (Department of Statistics & Data Science, Yale University) #
Discovering Exoplanets With Hermite-Gaussian Linear Regression
