Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Employer
- Monash University
- CNRS
- University of Colorado
- University of Glasgow
- ETH Zurich
- SUNY Polytechnic Institute
- Stony Brook University
- University of Sheffield
- Columbia University
- Heidelberg University
- Inria, the French national research institute for the digital sciences
- King Abdullah University of Science and Technology
- Oak Ridge National Laboratory
- Rice University
- SciLifeLab
- UNIVERSITY OF HELSINKI
- University of Bristol
- University of North Carolina at Chapel Hill
- University of Oslo
- University of Southern Denmark
- University of Toronto
- Zintellect
- AUSTRALIAN NATIONAL UNIVERSITY (ANU)
- Aalborg University
- Australian National University
- ETH Zürich
- French National Research Institute for Sustainable Development
- Friedrich Schiller University Jena
- Georgetown University
- Heriot Watt University
- Institut Pasteur
- Japan Agency for Marine-Earth Science and Technology
- Johns Hopkins University
- London School of Hygiene & Tropical Medicine;
- Ludwig-Maximilians-Universität München •
- Massachusetts Institute of Technology
- Max Planck Institutes
- National Centre for Nuclear Research
- Nature Careers
- Queen's University
- Rutgers University
- Simons Foundation/Flatiron Institute
- Technical University of Munich
- Tilburg University
- Tilburg University; 16 Oct ’25 published
- University Paul Sabatier
- University of A Coruña
- University of Adelaide
- University of Amsterdam (UvA)
- University of Amsterdam (UvA); yesterday published
- University of Birmingham
- University of Bristol;
- University of British Columbia
- University of California Davis
- University of California San Francisco
- University of California, Berkeley
- University of California, San Diego
- University of Idaho
- University of Leeds
- University of Leeds;
- University of London
- University of Luxembourg
- University of Miami
- University of Nebraska–Lincoln
- University of Texas at Austin
- University of Warwick
- University of Washington
- Université d'Orléans
- Utrecht University
- Utrecht University; Utrecht
- 60 more »
- « less
-
Field
-
on proving conditions under which such algorithms are optimal, and develop mathematical bounds on their sub-optimality in more complex cases. 3) Numerical Solutions to Bayesian Optimal Stopping Problems
-
Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 2 months ago
. The work will apply state-of-the-art three-dimensional atmospheric chemistry and circulation models, together with advanced statistical techniques (optimal Bayesian, Markov Chain-MonteCarlo, etc.) to solve
-
, clustering analyses, propagating location and other uncertainties...) of mid-ocean ridge catalogs, using standard, Bayesian and machine learning techniques. ⁃ Implement methodologies that improve estimates
-
factors. The LCSB recruits talented scientists from various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently
-
- identifying which measurements are most informative and guiding where, when and how to observe next. By combining Bayesian inference, probabilistic modeling, and machine learning, the project aims to make
-
, borehole data, geological mapping and other data) and produce estimates of the physical properties of the subsurface, and crucially, the associated uncertainty on those estimates. Initially, you will focus
-
non stationnaires. Dans ces représentations (STFT/ spectro- gramme, ondelettes, etc.), les composantes d'intérêt apparaissent sous forme de ridges. Estimer ces ridges suffit alors à reconstruire les
-
probability, partial differential equations, and mathematical physics. In statistics, these include biostatistics, optimal design, computer experiments, sequential analysis, shape-constrained inference, time
-
, simulations, and games, which use a variety of AI technologies to learn from, collaborate with, support, or improve humans; Deep Learning for Perception: Use of deep learning algorithms for computer vision
-
of parametrization of these models based on least squares and Bayesian calibration techniques employing longitudinal series of anonymized PSA data from patients. 3) Analysis of the predictions, parameters, and