Sort by
Refine Your Search
-
mathematical background Core skills: Probability and statistics. Estimation, Bayesian inference, uncertainty quantification and calibration (proper scoring rules, reliability diagrams, ECE), experiment design
-
Machine Learning Seminar Group Advanced Tutorial Lecture Series on Machine Learning Non-Parametric Bayes Tutorial Course (October 9, 16 and 28, 2008) Bayesian statistics in other labs Machine Learning and
-
Research and development of data-driven and probabilistic planning methods for informative and adaptive environmental sampling. Development of sensor-fusion-based estimation and environmental field
-
an interdisciplinary undertaking, involving biochemistry/structural biology, molecular and organismal genetics, biophysics, biostatistics, bioinformatics, and theoretical physics. Recently, AI (AlphaFold, computer