October 23, 2018 |
On the effectiveness of joint inversion Jodi Mead (Boise State University) |
Recent Advances in Machine Learning and Computational Methods for Geoscience |

October 26, 2018 |
Generalization and regularization in deep learning for nonlinear inverse problems Maarten De Hoop (Rice University) |
Recent Advances in Machine Learning and Computational Methods for Geoscience |

October 23, 2018 |
Machine Learning in Imaging and Inverse Problems: Where is it Going? Charles Bouman (Purdue University) |
Recent Advances in Machine Learning and Computational Methods for Geoscience |

October 24, 2018 |
Indomitable segmentation and pooling: A new perspective on clairvoyant fusion Alan Schaum (Naval Research Laboratory) |
Recent Advances in Machine Learning and Computational Methods for Geoscience |

October 24, 2018 |
Learning generative models of monostatic and bistatic synthetic aperture radar imagery Emre Ertin (The Ohio State University) |
Recent Advances in Machine Learning and Computational Methods for Geoscience |

October 24, 2018 |
Space-borne SAR interferometry: Three Decades of Innovation and Problem Solving Manoochehr Shirzaei (Arizona State University) |
Recent Advances in Machine Learning and Computational Methods for Geoscience |

October 24, 2018 |
GEO-AI - the birth of a new discipline Eldad Haber (University of British Columbia) |
Recent Advances in Machine Learning and Computational Methods for Geoscience |

October 25, 2018 |
Advances in Supervised and Semi-Supervised Machine Learning for Image Analysis of Multi-Modal Geospatial Imagery Data Saurabh Prasad (University of Houston) |
Recent Advances in Machine Learning and Computational Methods for Geoscience |

October 23, 2018 |
Impact of geological stress on flow and transport in fractured media Peter Kang (University of Minnesota, Twin Cities) |
Recent Advances in Machine Learning and Computational Methods for Geoscience |

October 24, 2018 |
Machine Learning for Background Estimation in Multispectral Imagery James Theiler (Los Alamos National Laboratory) |
Recent Advances in Machine Learning and Computational Methods for Geoscience |

October 22, 2018 |
Overview of today’s joint inversion methodology and its future into the machine-learning era for geophysical imaging Monica Maceira (Oak Ridge National Laboratory) |
Recent Advances in Machine Learning and Computational Methods for Geoscience |

October 25, 2018 |
Regularization and Compression via Tensor Dictionaries Misha Kilmer (Tufts University) |
Recent Advances in Machine Learning and Computational Methods for Geoscience |

October 22, 2018 |
Fast and Accurate Maximum-Likelihood Estimation of Parameterized Spectral Densities that Jointly Characterize Bivariate Two-Dimensional Random Fields Frederik Simons (Princeton University) |
Recent Advances in Machine Learning and Computational Methods for Geoscience |

October 23, 2018 |
Dictionary learning and graph signal processing on a 5200 element seismic array Peter Gerstoft (University of California, San Diego) |
Recent Advances in Machine Learning and Computational Methods for Geoscience |

October 22, 2018 |
Hierarchical deep generative networks for Bayesian inverse problems Pengchuan Zhang (Microsoft Research) |
Recent Advances in Machine Learning and Computational Methods for Geoscience |

October 25, 2018 |
Novel Machine Learning Methods for Extraction of Features Characterizing Complex Datasets and Models Velimir Vesselinov (Los Alamos National Laboratory) |
Recent Advances in Machine Learning and Computational Methods for Geoscience |

October 22, 2018 |
Geometric separation and applications to hyperspectral image analysis Demetrio Labate (University of Houston) |
Recent Advances in Machine Learning and Computational Methods for Geoscience |

March 29, 2018 |
Macroscale implications of optical conductivity: Dispersion by homogenization and curvature renormalization Dionisios Margetis (University of Maryland) |
Workshop on Theory and Computation for Transport Properties in 2D Materials |

March 26, 2018 |
Solid-state physics at the ballistic-to-hydrodynamic crossover. 1) Introduction Andrew Lucas (Stanford University) |
Workshop on Theory and Computation for Transport Properties in 2D Materials |

March 26, 2018 |
Nonlinear optics and hydrodynamics of graphene Michael Fogler (University of California, San Diego) |
Workshop on Theory and Computation for Transport Properties in 2D Materials |

March 26, 2018 |
Boltzmann-Langevin theory: Applications to Coulomb drag Alex Levchenko (University of Wisconsin, Madison) |
Workshop on Theory and Computation for Transport Properties in 2D Materials |

March 27, 2018 |
Hydrodynamic approach to interacting electrons Boris Narozhny (Karlsruhe Institute of Technology) |
Workshop on Theory and Computation for Transport Properties in 2D Materials |

March 27, 2018 |
Solid-state physics at the ballistic-to-hydrodynamic crossover. 2) Open problems Andrew Lucas (Stanford University) |
Workshop on Theory and Computation for Transport Properties in 2D Materials |

March 28, 2018 |
Charge transport in crystals at finite-temperature Emil Prodan (Yeshiva University) |
Workshop on Theory and Computation for Transport Properties in 2D Materials |

March 28, 2018 |
Chiral response of twisted bilayer graphene Tobias Stauber (Consejo Superior de Investigaciones Científicas (CSIC)) |
Workshop on Theory and Computation for Transport Properties in 2D Materials |

March 29, 2018 |
Chiral plasmon in gapped Dirac systems Tony Low (University of Minnesota, Twin Cities) |
Workshop on Theory and Computation for Transport Properties in 2D Materials |

March 29, 2018 |
Modeling and simulation of incommensurate 2D materials Eric Cances (École Nationale des Ponts-et-Chaussées (ENPC)) |
Workshop on Theory and Computation for Transport Properties in 2D Materials |

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 |

April 23, 2018 |
The local partial autocorrelation function and its use in forecasting Rebecca Killick (University of Lancaster) |
Forecasting from Complexity |

April 25, 2018 |
Nonparametric inference for Hawkes processes. Applications for estimating functional connectivity graphs of neurons. Vincent Rivoirard (Université Paris-Dauphine) |
Forecasting from Complexity |

April 23, 2018 |
High-dimensional Linear Regression for Dependent Observations with Application to Nowcasting Ruey Tsay (University of Chicago) |
Forecasting from Complexity |

April 25, 2018 |
Dynamic Filtering of Time-Varying Sparse Signals Christopher Rozell (Georgia Institute of Technology) |
Forecasting from Complexity |

April 23, 2018 |
Sparse Identification and Estimation of High-Dimensional Vector AutoRegressive Moving Averages Ines Wilms (Katholieke Universiteit Leuven) |
Forecasting from Complexity |

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 |

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 |

March 05, 2018 |
Local keynote lecture: Ways of Knowing in HCI Haiyi Zhu (University of Minnesota, Twin Cities) |
Women in Data Science (WiDS) Conference |

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 |

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 |

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 |

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 |

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 |