#uncertaintyquantification search results
NEW ISSUE ALERT: Vol. 15, Issue 6 International Journal for Uncertainty Quantification is out! Multigrid meets Monte Carlo, Bayesian calibration for unseen outputs & operator learning that quantifies its own errors. dl.begellhouse.com/journals/52034… #UncertaintyQuantification
On Singular Bayesian Inference of Underdetermined Quantities—Part I: Invariant Discrete Ill-Posed Inverse Problems in Small and Large Dimensions mdpi.com/2673-9984/12/1… By Fabrice Pautot From the MaxEnt 2024 #BayesianInference #UncertaintyQuantification @MdpiPhysci
NEW ISSUE ALERT: Vol. 15, Issue 6 International Journal for Uncertainty Quantification is out! Multigrid meets Monte Carlo, Bayesian calibration for unseen outputs & operator learning that quantifies its own errors. dl.begellhouse.com/journals/52034… #UncertaintyQuantification
On the SIAM News blog, Lorenzo Tamellini, Yueting Li, Chiara Piazzola, and Claudia Zoccarato utilize #uncertaintyquantification to help with land subsidence and improve groundwater exploitation policy in the Guadalentín Basin aquifer. Read more! #SIAMCSE25 siam.org/publications/s…
📚 A Framework for #MultiPhysics Modeling, Design Optimization and #UncertaintyQuantification of Fast-Spectrum Liquid-Fueled #MoltenSalt #Reactors 🔗 mdpi.com/2076-3417/14/1… 👨🔬 by David Holler et al. 🏫 @NCState #sensitivityanalysis #CFD
Conformal Approach to Gaussian Process Surrogate Evaluation with Marginal Coverage Guarantees dl.begellhouse.com/journals/55804… #MachineLearning #UncertaintyQuantification #BayesianMachineLearning
Concurrent, Condensed Stein Variational Gradient Descent for Uncertainty Quantification of Neural Networks dl.begellhouse.com/journals/55804… #SteinVariationalInference #BayesianNeuralNetworks #UncertaintyQuantification
Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation dl.begellhouse.com/journals/55804… #UncertaintyQuantification #NormalizingFlows #MachineLearningForScience
Solving #UncertaintyQuantification problems on realistic models can be computationally challenging. In SIAM News, Linus Seelinger and Anne Reinarz introduce UM-Bridge: an interface that provides a link between any UQ code and model #software. Read more: sinews.siam.org/Details-Page/l…
Our PhD student Priyanka presented her research work on #UncertaintyQuantification of complex thin-walled #composites which has attracted a significant interest, in the #ICCMS conference held recently at #IITMandi #womeninSTEM
Validation and uncertainty quantification for digital twins workshop at the UK Atomic Energy Authority in June: bringing together computational and experimental mechanics communities. bssm.org/events/worksho… #digitaltwin #uncertaintyquantification @UKAEAofficial
#mdpitopics 📢@Aerospace_MDPI, @Applsci, @batteriesmdpi, @energies_mdpi, @JMSE_MDPI, @Machines_MDPI, @MathematicsMDPI, and @Sensors_MDPI journals organized a topic "#UncertaintyQuantification in Design, Manufacturing and Maintenance of Complex Systems". 👉mdpi.com/topics/5H23414…
On the SIAM News blog, James Berger and Leonard Smith illustrate the strengths and weaknesses of the #statistical formalism and the ensemble approach to #UncertaintyQuantification, delineating both their successes and remaining challenges. Read more: siam.org/publications/s…
Agenda now published - take a look and secure your place: bssm.org/events/worksho… @UKAEAofficial #experimentalmechanics #digitaltwin #uncertaintyquantification
Bayesian methods quantify uncertainty in predictions, not just point estimates. Knowing confidence matters as much as knowing predictions. Probabilistic intelligence. #MachineLearningAlgorithms #BayesianML #UncertaintyQuantification
CASC R&D group highlight: The UQ Optimization Group researches at the intersection of #Math, #ComputerScience, & applied science & engineering to enable large-scale optimization, control, & #UncertaintyQuantification for complex systems. computing.llnl.gov/casc/uq-optimi… #computing
📢 Excited to share our latest research on the intersection of #ExplainableAI (XAI) & #UncertaintyQuantification (UQ) for Predictive Process Monitoring! 1️⃣ UQ in ML explanations (bit.ly/3L4WXTS) 2️⃣ XAI uncovers drivers of ML model uncertainty (bit.ly/3LqipUL)
Our guest professor Jonathan Bamber @jlbamber on #UncertaintyQuantification talks about spatio-temporal inference applied to global sea level trends. #AI4EOSymposium2023
Addressing the challenges and introducing a new approach to manage uncertainty in long-text generation by LLMs. #UncertaintyQuantification #LLMs #Longtextgeneration
On Singular Bayesian Inference of Underdetermined Quantities—Part I: Invariant Discrete Ill-Posed Inverse Problems in Small and Large Dimensions mdpi.com/2673-9984/12/1… By Fabrice Pautot From the MaxEnt 2024 #BayesianInference #UncertaintyQuantification @MdpiPhysci
🔗 iopscience.iop.org/article/10.108… Joint work with the great @TheDeysiGuy, David Zhao, Brett Andrews, Jeff Newman, and Ann Lee. #MachineLearning #Calibration #UncertaintyQuantification #IA #Astronomy
On the SIAM News blog, Lorenzo Tamellini, Yueting Li, Chiara Piazzola, and Claudia Zoccarato utilize #uncertaintyquantification to help with land subsidence and improve groundwater exploitation policy in the Guadalentín Basin aquifer. Read more! #SIAMCSE25 siam.org/publications/s…
📚 A Framework for #MultiPhysics Modeling, Design Optimization and #UncertaintyQuantification of Fast-Spectrum Liquid-Fueled #MoltenSalt #Reactors 🔗 mdpi.com/2076-3417/14/1… 👨🔬 by David Holler et al. 🏫 @NCState #sensitivityanalysis #CFD
Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation dl.begellhouse.com/journals/55804… #UncertaintyQuantification #NormalizingFlows #MachineLearningForScience
Bayesian methods quantify uncertainty in predictions, not just point estimates. Knowing confidence matters as much as knowing predictions. Probabilistic intelligence. #MachineLearningAlgorithms #BayesianML #UncertaintyQuantification
NEW ISSUE ALERT: Vol. 15, Issue 6 International Journal for Uncertainty Quantification is out! Multigrid meets Monte Carlo, Bayesian calibration for unseen outputs & operator learning that quantifies its own errors. dl.begellhouse.com/journals/52034… #UncertaintyQuantification
NEW ISSUE ALERT: Vol. 15, Issue 6 International Journal for Uncertainty Quantification is out! Multigrid meets Monte Carlo, Bayesian calibration for unseen outputs & operator learning that quantifies its own errors. dl.begellhouse.com/journals/52034… #UncertaintyQuantification
Concurrent, Condensed Stein Variational Gradient Descent for Uncertainty Quantification of Neural Networks dl.begellhouse.com/journals/55804… #SteinVariationalInference #BayesianNeuralNetworks #UncertaintyQuantification
Uncertainty quantification is an important step in establishing the predictive accuracy of simulation models employed in a broad range of disciplines. 📚mngbookshop.co.uk/9781611977837/… Browse Mathematics: mngbookshop.co.uk/mng-subject-hi… @TheSIAMNews #UncertaintyQuantification
Conformal Approach to Gaussian Process Surrogate Evaluation with Marginal Coverage Guarantees dl.begellhouse.com/journals/55804… #MachineLearning #UncertaintyQuantification #BayesianMachineLearning
Post-Hoc Split-Point Self-Consistency Verification for Efficient, Unified Quantification of Aleatoric and Epistemic U... 👥 Zhizhong Zhao & Ke Chen #UncertaintyQuantification #DeepLearning #AIResearch #MachineLearning #OpenSource 🔗 trendtoknow.ai
📢 New Publication in #Forecasting 📖 Comparative Analysis of Physics-Guided Bayesian Neural Networks for Uncertainty Quantification in Dynamic Systems ✍️ By Xinyue Xu & Julian Wang 🔗 brnw.ch/21wVHNw #BayesianNeuralNetworks #UncertaintyQuantification #DynamicSystems
Just wrapped our 16th summer school on #UncertaintyQuantification! 27 researchers explored Monte Carlo methods & model robustness in chem eng, energy, & data science. What’s your take on shaking model foundations? Read more: tinyurl.com/jyv7bcxk #MonteCarlo…
🎙️ AI Frontiers: Machine Learning Breakthroughs (2025-08-18) – Trust, Scale & Collaboration #AI #MachineLearning #UncertaintyQuantification Watch full episode: youtube.com/watch?v=m3Cg6-…
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AI Frontiers: Machine Learning Breakthroughs (2025-08-18) – Trust,...
New SIAM Book: Computational Uncertainty Quantification for Inverse Problems! Learn more: bookstore.siam.org/cs19 #uncertaintyquantification
We are at the #orbitaldebris2019 conference organised by @NASA. Our first presentation on #CAM computation and #uncertaintyquantification by @JuanLGonzalo @GigiDiLizia and @camilla_colombo @AerospacePoliMI @polimi @ERC_Research
#UncertaintyQuantification in #imageRetrieval is crucial for downstream decisions! In our #ICCV2021 📰, we model embeddings as distributions rather than points, such that data uncertainty is propagated to retrieval. We mirror the triplet loss, and learn stochastic features.🧵1/4
During today's @M2D_Network event we'll be welcoming psychologists, philosophers, social scientists, economists, engineers, climate scientists and more to #INI. Very inspiring how diverse the applications of the #UncertaintyQuantification programme can be #cambridge #mathematics
This week marks the start of the UNQ programme - the Institute's first of 2018! Full details can be found via the following link: newton.ac.uk/event/unq #uncertaintyquantification #mathematics #research #cambridge
Uncertainty quantification for cardiac models workshop part of the #FickleHeart programme just kicking off. Looking forward to hearing how #UncertaintyQuantification is helping translate cardiac models to clinical applications
More #cardiac #uncertaintyquantification posters
They’re a number of posters on show today as part of Industrial and Clinical Application of Cardiac Simulations: Quantifying Uncertainty in Model Predictions gateway.newton.ac.uk/event/ofbw45
📚 A Framework for #MultiPhysics Modeling, Design Optimization and #UncertaintyQuantification of Fast-Spectrum Liquid-Fueled #MoltenSalt #Reactors 🔗 mdpi.com/2076-3417/14/1… 👨🔬 by David Holler et al. 🏫 @NCState #sensitivityanalysis #CFD
In our latest #study we develop an #UncertaintyQuantification (#UQ) #Framework for #ScaleResolving #Turbulence #Simulations and apply it to 2 #CFD codes: #Nek5000 and #OpenFOAM!! #Article: sciencedirect.com/science/articl… #Code: joss.theoj.org/papers/10.2110… #research #datascience #data
The UNQ programme's second workshop ("Surrogate models for UQ in complex systems") has kicked off today here at INI. Click for full schedule and live stream links: newton.ac.uk/events/streami… #mathematics #cambridge #uncertaintyquantification #UQ #research
Interested in learning how you can use code for #uncertaintyquantification, #numericaloptimisation, #dimensionreduction, #numericalintegration, #surrogatemodeling & #sensitivityanalysis? Join the #EffectiveQuadratures workshop on 1 July: bit.ly/2WAg7qf
#NewtonEBD2019 participants have been getting down to some serious (and colourful) maths this week proving #UncertaintyQuantification results to improve landscape decision making.
Full listings and live stream links for this week's workshop, "Key UQ methodologies and motivating applications". Starts at 10:00 UTC: newton.ac.uk/events/seminar… #uncertaintyquantification #mathematics #research #cambridge
New Release: Handbook on #Statistical Design & Analysis Techniques for Modeling & Simulation Validation idalink.org/TS_Handbook. For additional content, visit idalink.org/Test_Science. #UncertaintyQuantification #Validation
On the SIAM News blog, Lorenzo Tamellini, Yueting Li, Chiara Piazzola, and Claudia Zoccarato utilize #uncertaintyquantification to help with land subsidence and improve groundwater exploitation policy in the Guadalentín Basin aquifer. Read more! #SIAMCSE25 siam.org/publications/s…
Validation and Improvement of a Bicycle #CrankArm Based in Numerical Simulation and #UncertaintyQuantification 👉 mdpi.com/1424-8220/20/7… #StrainGauges #metamodel #StatisticalValidation #FatigueTest
Solving #UncertaintyQuantification problems on realistic models can be computationally challenging. In SIAM News, Linus Seelinger and Anne Reinarz introduce UM-Bridge: an interface that provides a link between any UQ code and model #software. Read more: sinews.siam.org/Details-Page/l…
CASC R&D group highlight: The UQ Optimization Group researches at the intersection of #Math, #ComputerScience, & applied science & engineering to enable large-scale optimization, control, & #UncertaintyQuantification for complex systems. computing.llnl.gov/casc/uq-optimi… #computing
#mdpitopics 📢@Aerospace_MDPI, @Applsci, @batteriesmdpi, @energies_mdpi, @JMSE_MDPI, @Machines_MDPI, @MathematicsMDPI, and @Sensors_MDPI journals organized a topic "#UncertaintyQuantification in Design, Manufacturing and Maintenance of Complex Systems". 👉mdpi.com/topics/5H23414…
It's turn for the coordinator of our project, @pablolamata to talk about his vision of the #VirtualTwin paradigm embedded in the #UncertaintyQuantification workshop. How much uncertainty is acceptable in clinical decisions? 🤔
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