Event Content - (B)

First Letter

(1) | 2 (2) | 5 (1) | A (22) | B (15) | C (19) | D (22) | E (30) | F (17) | G (11) | H (6) | I (6) | J (4) | K (2) | L (8) | M (19) | N (6) | O (15) | P (11) | Q (4) | R (14) | S (33) | T (24) | U (3) | V (3) | W (8)

	Dec 9, 12:00 - 13:00, Backward Error Analysis for Nonlinear Differential Equations (KAUST), David Ketcheson, Professor, Applied Mathematics and Computational Science	Graduate Seminar
	Jan 27, 12:00 - 13:00, Backward induction: from theory to empirics (KAUST), Konrad Grabiszewski, Instructional Professor, Applied Mathematics and Computational Sciences	Graduate Seminar
	Mar 6, 12:00 - 13:00, Bayesian Deep Learning (B9 L3 R3128), Maurizio Filippone, Associate Professor, EURECOM, France	Bayesian computational statistics, Deep learning, Graduate Seminar
	Oct 14, 16:30 - 17:45, Bayesian image analysis in Fourier space (BIFS) models and some relationships with Markov random fields (B4 B5 A0215), Prof. John Kornak, Biostatistics, University of California, San Francisco	bayesian analysis, Seminar
	Mar 3, 10:00 - 12:00, Bayesian Inference for Partially Observed Continuous-Time Processes (B5 L5 R5220), Amin Wu, Ph.D., Statistics	bayesian inference, markov chains, McKean-Vlasov SDEs, Monte Carlo
	Apr 5, 15:00 - 17:00, Bayesian Modeling of Sub-Asymptotic Spatial Extremes (B5 L5 R5220), Rishikesh Yadav, Ph.D. Student, Statistics	bayesian inference, extreme-value theory, spatial statistics, spatio-temporal statistics, Ph.D. Dissertation Defense
	Jan 5, 17:00 - 19:00, Bayesian Non-parametric Models for Time Series Decomposition (B1 R4214), Guillermo C. Granados Garcia, Ph.D. Student, Statistics	spectral density function, Ph.D. Dissertation Defense
	Nov 24, 15:00 - 16:00, Bayesian Regression Trees, Nonparametric Heteroscedastic Regression Modeling and MCMC Sampling (B1 L2), Matthew Pratola, Assistant Professor of Statistics, The Ohio State University	Bayesian Statistics, nonparametric statistics, Seminar
	May 14, 14:00 - 16:00, Bayesian Spatio-Temporal Modeling for Environmental Monitoring and Epidemiology: Disaggregation and Disease Spread Dynamics (B3 R5220), Fernando Rodriguez Avellaneda, Ph.D. Student, Statistics	Ph.D. Dissertation Defense
	Jun 27, 18:00 - 20:00, Better Methods and Theory for Federated Learning: Compression, Client Selection, and Heterogeneity (B5 L5 R5209), Samuel Horváth, Ph.D. Student, Statistics	Federated learning, Optimization for Machine Learning, Ph.D. Dissertation Defense
	Jan 28, 12:00 - 13:00, Beyond Bayesian Uncertainty: a Variational Perspective (B4/5 L0 A0215), Chérief-Abdellatif Badr-Eddine, CNRS (Chargé de Recherche) Researcher, Laboratoire de Probabilités, Statistique et Modélisation (LPSM), Sorbonne Université, France	Seminar
	Oct 16, 12:00 - 13:00, Bias-Reduced Estimation of Structural Equations Models (B9 L2 R2325), Haziq Jamil, Research Specialist, Statistics	Graduate Seminar
	Nov 24, 09:00 - 10:00, BICNet: A Bayesian Approach for Estimating Task Effects on Intrinsic Connectivity Networks in fMRI Data (KAUST), Meini Tang, M.S. Student, Statistics	Thesis Defense
	Apr 14, 12:00 - 13:00, Biomedical research: a world of statistical challenges (B9 L2 H2), Prof. David Gomez-Cabrero, Biological, Environmental Science and Eng, KAUST	Graduate Seminar
	Oct 9, 12:00 - 13:00, Block Low-Rank Matrices for Modern Scientific Computing (B9 L2 R2325), Daria Sushnikova, Postdoctoral Research Fellow, Computer, Electrical and Mathematical Sciences and Engineering	Graduate Seminar