Event Content - (R)

First Letter

2 (2) | 5 (1) | A (17) | B (10) | C (17) | D (18) | E (24) | F (13) | G (7) | H (6) | I (6) | J (4) | K (1) | L (6) | M (17) | N (3) | O (11) | P (11) | Q (4) | R (8) | S (28) | T (16) | U (1) | V (1) | W (7)

	Sep 29, 13:00 - 14:00, Randomized multilevel Monte Carlo for inference (KAUST), Kody J.H. Law, Professor, Applied Mathematics in the Department of Mathematics, University of Manchester and Manchester Institut	Seminar
	Apr 28, 16:30 - 17:30, Recent approaches for flexible and efficient analysis of non-stationary time series (B2 B3 A0215), Prof. Raquel Prado, Department of Statistics, University of California	Seminar
	Oct 28, 12:00 - 13:00, Recent progress on symbolic computation for PDE and their numerical schemes (KAUST), Diogo Gomes, Program Chair, Applied Mathematics and Computational Sciences	Graduate Seminar
	Mar 24, 12:00 - 13:00, Regression models for count and proportion data (B9 L2 H2), Alexandre de Bustamante Simas , Research Scientist, Statistics	Graduate Seminar
	Apr 19, 16:00 - 18:00, Regularized Regression for Survival Data: Methods and Applications (B1 L4 R4102), Yi Li, Professor, Biostatistics, University of Michigan	Lecture
	Nov 4, 16:00 - 17:00, Reproducibility in Computer Science - Part 1 (B9 L3 R3223), Roy Maxion, Research Professor, Computer Science Department, Carnegie Mellon University	artificial intelligence, complex models, Computer science, machine learning, reliability testing, reproducibility issues, scientific enterprise, Workshop
	Nov 5, 16:00 - 17:00, Reproducibility in Computer Science - Part 2 (B9 L3 R3223), Roy Maxion, Research Professor, Computer Science Department, Carnegie Mellon University	artificial intelligence, complex models, Computer science, machine learning, reliability testing, reproducibility issues, scientific enterprise, Workshop
	Nov 6, 16:00 - 17:00, Reproducibility in Computer Science - Part 3 (B9 L3 R3223), Roy Maxion, Research Professor, Computer Science Department, Carnegie Mellon University	artificial intelligence, complex models, Computer science, machine learning, reliability testing, reproducibility issues, scientific enterprise, Workshop