Campuses:

Talks

Date Title / Speaker Eventsort ascending
April 26, 2018 Inference for Spatio-Temporal Changes of Arctic Sea Ice
Noel Cressie (University of Wollongong)
Forecasting from Complexity
April 23, 2018 School of Math Ordway Distinguished Lecture: Applied Random Matrix Theory
Joel Tropp
Forecasting from Complexity
April 26, 2018 Stochastic Simulation of Predictive Space-Time Scenarios of Wind Speed Using Observations and Physical Models
Mihai Anitescu (Argonne National Laboratory)
Forecasting from Complexity
April 24, 2018 Assessing Internal Climate Variability with Few Ensemble Runs
Dorit Hammerling (NCAR)
Forecasting from Complexity
April 26, 2018 Non-parametric Sparse Additive Auto-regressive Network Models
Garvesh Raskutti (University of Wisconsin, Madison)
Forecasting from Complexity
April 24, 2018 Generating Calibrated Ensembles of Physically Realistic, High-Resolution Precipitation Forecast Fields Based on GEFS Model Output
Michael Scheuerer (National Oceanographic and Atmospheric Administration (NOAA))
Forecasting from Complexity
April 25, 2018 Estimation of inhomogeneous point processes: Theory and applications
Mark Davenport (Georgia Institute of Technology)
Forecasting from Complexity
April 27, 2018 Spatio-Temporal Point Process Models for Ambulance Demand
David S. Matteson (Cornell University)
Forecasting from Complexity
April 26, 2018 Multi-class modelling for muscle level prediction of beef eating quality
Garth Tarr (University of Sydney)
Forecasting from Complexity
April 26, 2018 Dynamic Shrinkage Processes
Daniel Kowal (Rice University)
Forecasting from Complexity
April 24, 2018 Bayesian Calibration of Multistate Stochastic Simulators
Oksana Chkrebtii (The Ohio State University)
Forecasting from Complexity
April 26, 2018 Fast Simulation based Estimation for Complex Models
Maria-Pia Victoria-Feser (Universite de Geneve)
Forecasting from Complexity
April 24, 2018 Spectral analysis for comparison of second-order flow structure in DNS simulations
Charlotte Haley (Argonne National Laboratory)
Forecasting from Complexity
April 26, 2018 Geometric Statistics for High-Dimensional Data Analysis
Singdhansu (Ansu) Chatterjee (University of Minnesota, Twin Cities)
Forecasting from Complexity
April 24, 2018 Spatiotemporal modelling of ocean surface velocities from drifters
Adam Sykulski (University of Lancaster)
Forecasting from Complexity
April 27, 2018 Optimal Dimension Reduction for Vector and Functional Time Series
Marc Hallin (Université Libre de Bruxelles)
Forecasting from Complexity
April 24, 2018 Network Estimation from Point Process Data
Rebecca Willett (University of Wisconsin, Madison)
Forecasting from Complexity
April 27, 2018 Regularized Estimation in High-dimensional Time Series Models
Sumanta Basu (Cornell University)
Forecasting from Complexity
April 24, 2018 Robust maximum association estimators
Peter Filzmoser (Technische Universität Wien)
Forecasting from Complexity
April 26, 2018 Half-spectral space-time models
Joe Guinness (North Carolina State University)
Forecasting from Complexity
April 25, 2018 Forecasting Realized Volatility Measures with Multivariate and Univariate Models: The Case of The US Banking Sector
Alain Hecq (Universiteit Maastricht (Rijksuniversiteit Limburg))
Forecasting from Complexity
April 27, 2018 Relevant parameter changes in structural break models
Arnaud Dufays (Laval University)
Forecasting from Complexity
April 24, 2018 Sequential change-point detection for Hawkes processes over networks
Yao Xie (Georgia Institute of Technology)
Forecasting from Complexity
April 23, 2018 Complexity vs Parsimony: The Challenge of Building Effective Nonlinear Dynamical Spatio-Temporal Forecasting Model
Chris Wikle (University of Missouri)
Forecasting from Complexity
April 25, 2018 Verification within Complexity: Comparing Spatial Fields
Eric Gilleland (National Center for Atmospheric Research)
Forecasting from Complexity
April 23, 2018 Fast spike train inference via l0 optimization
Daniela Witten (University of Washington)
Forecasting from Complexity
April 25, 2018 Deep Spatial Learning for Forensic Geolocation with Microbiome Data
Brian Reich (North Carolina State University)
Forecasting from Complexity
March 05, 2018 Local keynote lecture: Ways of Knowing in HCI
Haiyi Zhu (University of Minnesota, Twin Cities)
Women in Data Science (WiDS) Conference
March 05, 2018 Local keynote lecture: Reinforcement learning for functional state space with application to Type 1 Diabetes
Susan Wei (University of Minnesota, Twin Cities)
Women in Data Science (WiDS) Conference
August 13, 2018 An Introduction to Multi-D Persistent Homology
Michael Lesnick (Princeton University)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 13, 2018 Morse Theory and Persistent Homology Computation
Gregory Henselman (University of Pennsylvania)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 14, 2018 Computation of Persistent Homology, Part II
Ulrich Bauer (Technical University of Munich)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 14, 2018 Quiver Representation Theory + Multiparameter Persistence
Magnus Botnan (Vrije Universiteit Amsterdam)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 14, 2018 Visualizing Two-parameter Persistence
Matthew Wright (St. Olaf College)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 14, 2018 Computing Minimal Presentations of Bipersistence Modules in Cubic Time
Michael Lesnick (Princeton University)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 14, 2018 Statistics for a Computational Topologist, Part I
Brittany Terese Fasy (Montana State University)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 15, 2018 Multiparameter Interleavings
Magnus Botnan (Vrije Universiteit Amsterdam)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 15, 2018 Software Tutorial
Michael Lesnick (Princeton University), Matthew Wright (St. Olaf College)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 15, 2018 Computation with Degree-Rips Bifiltrations
Roy Zhao (University of California, Berkeley)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 15, 2018 Statistics for a Computational Topologist Part II
Brittany Terese Fasy (Montana State University)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 15, 2018 Two-Parameter Persistence for Virtual Ligand Screening
Bryn Keller (Intel Corporation)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 13, 2018 Introduction to Persistent Homology
Matthew Wright (St. Olaf College)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 13, 2018 Applications of Persistence
Lori Ziegelmeier (Macalester College)
Tutorial on Multiparameter Persistence, Computation, and Applications
August 13, 2018 Computation of Persistent Homology, Part I
Ulrich Bauer (Technical University of Munich)
Tutorial on Multiparameter Persistence, Computation, and Applications
February 21, 2018 Dynamic landmark prediction for genetic mixture models
Tanya Garcia (Texas A & M University)
Frontiers in Forecasting
February 21, 2018 Sparse Vector Autoregressive Models
Christophe Croux (EDHEC Business School)
Frontiers in Forecasting
February 22, 2018 Extended ensemble Kalman filters for high-dimensional hierarchical state-space models
Matthias Katzfuss (Texas A & M University)
Frontiers in Forecasting
February 22, 2018 Forecasting large collections of times series
George Athanasopoulos (Monash University)
Frontiers in Forecasting
February 22, 2018 Interpretable Deep Learning Models for Forecasting
Yan Liu (University of Southern California)
Frontiers in Forecasting
February 22, 2018 Panel: Advanced Business Analytics and Forecasting at BASF
Sven Serneels (BASF Corporation)
Frontiers in Forecasting
February 22, 2018 High-dimensional Multivariate Time Series with Additional Structure
Katherine Ensor (Rice University)
Frontiers in Forecasting
February 22, 2018 Spectral analysis of high-dimensional time series with applications to the mean-variance frontier
Alexander Aue (University of California, Davis)
Frontiers in Forecasting
February 23, 2018 Conditional Adaptive Bayesian Spectral Analysis of Nonstationary Biomedical Time Series
Robert Krafty (University of Pittsburgh)
Frontiers in Forecasting
February 22, 2018 Factor Augmented Vector Autoregressive Models under High Dimensional Scaling
George Michailidis (University of Florida)
Frontiers in Forecasting
February 21, 2018 A longitudinal Bayesian model for spectral analysis of neuroimaging time series data
Mark Fiecas (University of Minnesota, Twin Cities)
Frontiers in Forecasting
February 22, 2018 Methods for estimating network change points for multivariate time series
Ivor Cribben (University of Alberta)
Frontiers in Forecasting
February 21, 2018 Predictive effect of economic and market variations on structural breaks in credit market
Haipeng Xing (State University of New York, Stony Brook (SUNY))
Frontiers in Forecasting
February 23, 2018 Models for Time Series of Counts with Shape Constraints
Richard Davis (Columbia University)
Frontiers in Forecasting
February 23, 2018 High-dimensiona Classification for Spatially Dependent Data
Tapabrata (Taps) Maiti (Michigan State University)
Frontiers in Forecasting
February 23, 2018 Sequential change-point detection based on nearest neighbors
Hao Chen (University of California, Davis)
Frontiers in Forecasting
February 21, 2018 Global multivariate point pattern models for rain type occurrence and its extension to spatio-temporal domain
Mikyoung Jun (Texas A & M University)
Frontiers in Forecasting
February 23, 2018 High-Dimensional Bayesian Geostatistics
Sudipto Banerjee (University of California, Los Angeles)
Frontiers in Forecasting
February 21, 2018 Learning Connectivity Networks from High-Dimensional Point Processes
Ali Shojaie (University of Washington)
Frontiers in Forecasting
February 23, 2018 Lensing and de-lensing the cosmic microwave background
Ethan Anderes (University of California, Davis)
Frontiers in Forecasting
February 21, 2018 Variable Targeting and Reduction in High-Dimensional Vector Autoregressions
Tucker McElroy (U.S. Bureau of the Census)
Frontiers in Forecasting
February 21, 2018 Semi-parametric Dynamic Max-copula Model for Multivariate Time Series
Zhengjun Zhang (University of Wisconsin, Madison)
Frontiers in Forecasting
May 29, 2018 Modeling Prion Replication within a Growing Yeast Population
Suzanne Sindi (University of California, Merced)
Workshop for Women in Mathematical Biology
May 29, 2018 A Mathematical Model for Enzyme Clustering in Glucose Metabolism
Hye-Won Kang (University of Maryland Baltimore County)
Workshop for Women in Mathematical Biology
May 30, 2018 Variability of Calcium Dynamics in Brain Astrocyte Cells
Alla Borisyuk (The University of Utah)
Workshop for Women in Mathematical Biology
May 30, 2018 Piecewise smooth maps for the circadian modulation of sleep-wake dynamics
Victoria Booth (University of Michigan)
Workshop for Women in Mathematical Biology
May 30, 2018 Direct and indirect effects of species interactions in disease systems
Zoi Rapti (University of Illinois at Urbana-Champaign)
Workshop for Women in Mathematical Biology
May 30, 2018 Glioblastoma recurrence and the role of MGMT promoter methylation
Katie Storey (University of Minnesota, Twin Cities)
Workshop for Women in Mathematical Biology
May 30, 2018 Multiscale Modeling of Axonal Cytoskeleton Dynamics in Diseases
Chuan Xue (The Ohio State University)
Workshop for Women in Mathematical Biology
May 30, 2018 Cytoskeletal mechanics of asymmetrically dividing cells: a mathematical modelling perspective
Blerta Shtylla (Pomona College)
Workshop for Women in Mathematical Biology
May 31, 2018 Embracing complexity of the tumor microenvironment for personalized medicine
Katarzyna Rejniak (Moffitt Cancer Center)
Workshop for Women in Mathematical Biology
May 31, 2018 A Mathematical Model of the Bivalent Binding of Thrombin to Fibrin
Karin Leiderman (Colorado School of Mines)
Workshop for Women in Mathematical Biology
May 31, 2018 Flagellated micro-swimmers in a viscous fluid
Sookkyung Lim (University of Cincinnati)
Workshop for Women in Mathematical Biology
May 29, 2018 Parameter identifiability and uncertainty in modeling infectious disease interventions
Marisa Eisenberg (University of Michigan)
Workshop for Women in Mathematical Biology
May 29, 2018 Parameter uncertainty quantification using surrogate models applied to a spatial model of yeast mating polarization
Ching-Shan Chou (The Ohio State University)
Workshop for Women in Mathematical Biology
May 29, 2018 Identifying robust cancer treatment protocols from small experimental datasets
Jana Gevertz (The College of New Jersey)
Workshop for Women in Mathematical Biology
March 07, 2018 Virtual Patients Derived from the CareLink Database
Benyamin Grosman (Medtronic)
Integrating Machine Learning and Predictive Simulation: From Uncertainty Quantification to Digital Twins
March 07, 2018 Brain clouds and Diffeomorphimetry in the soft condensed matter continuum
Michael Miller (Johns Hopkins University)
Integrating Machine Learning and Predictive Simulation: From Uncertainty Quantification to Digital Twins
March 07, 2018 Incorporating simulated virtual patient outcomes as prior information in medical device clinical trials
Adam Himes (Medtronic)
Integrating Machine Learning and Predictive Simulation: From Uncertainty Quantification to Digital Twins
March 08, 2018 Physics-Constrained Data-Driven Modeling : A Vision for Prediction, Design and Operation of Complex Systems
Karthik Duraisamy (University of Michigan)
Integrating Machine Learning and Predictive Simulation: From Uncertainty Quantification to Digital Twins
March 08, 2018 Using Simulations for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction
Garrett Goh (Pacific Northwest National Laboratory)
Integrating Machine Learning and Predictive Simulation: From Uncertainty Quantification to Digital Twins
March 06, 2018 Enabling High-Fidelity Digital Twins of Critical Assets via Reduced Order Modeling
David Knezevic (Akselos)
Integrating Machine Learning and Predictive Simulation: From Uncertainty Quantification to Digital Twins
March 06, 2018 Connecting physics based and data driven models: the best of two worlds
Herman van der Auweraer (Siemens)
Integrating Machine Learning and Predictive Simulation: From Uncertainty Quantification to Digital Twins
March 06, 2018 Predicting Rare Events in Complex Systems
Tuhin Sahai (United Technologies Corporation)
Integrating Machine Learning and Predictive Simulation: From Uncertainty Quantification to Digital Twins
March 06, 2018 Globally Optimal, Data-Driven Symbolic Discovery
Lior Horesh (IBM)
Integrating Machine Learning and Predictive Simulation: From Uncertainty Quantification to Digital Twins
March 06, 2018 Understanding the Simulation Revolution
Joe Walsh (ASSESS Initiative)
Integrating Machine Learning and Predictive Simulation: From Uncertainty Quantification to Digital Twins
March 07, 2018 Understanding and predicting physiological resistance with simulation and topological analysis
Drew Pruett (University of Mississippi)
Integrating Machine Learning and Predictive Simulation: From Uncertainty Quantification to Digital Twins
December 05, 2017 Snow Business: Scientific Computing in the Movies and Beyond
Joseph Teran (University of California, Los Angeles)
Public Lecture Series
February 21, 2018 Impossible Objects: The Mathematics of 3D Illusions
Kokichi Sugihara (Meiji University)
Public Lecture Series
October 27, 2017 Phaseless reconstruction: A frame theoretical approach, Part 1
Dongmian Zou (University of Minnesota, Twin Cities)
Postdoc Seminar Series
November 03, 2017 Phaseless reconstruction: A frame theoretical approach, Part 2
Dongmian Zou (University of Minnesota, Twin Cities)
Postdoc Seminar Series
November 10, 2017 Improved support recovery guarantees for the group Lasso with applications to structural health monitoring
Mojtaba Elyaderani (3M)
Postdoc Seminar Series
September 22, 2017 Local Inversion-Free covariance estimation for Gaussian Spatial Processes
Hossein Keshavarz (University of Minnesota, Twin Cities)
Postdoc Seminar Series
November 17, 2017 Optimal Control of Nonholonomic Mechanical Systems
Stuart Rogers (University of Minnesota, Twin Cities)
Postdoc Seminar Series
December 01, 2017 Lecture
Stuart Rogers (University of Minnesota, Twin Cities)
Postdoc Seminar Series
September 29, 2017 Online change-point detection in high dimensional Gaussian graphical models
Hossein Keshavarz (University of Minnesota, Twin Cities)
Postdoc Seminar Series

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