Top Tweets for #Uncertaintyquantification
International Journal for Uncertainty Quantification #JCR2026 metrics:
📈 Impact Factor: 1.6
📊 CiteScore: 3.4
🏆 Q1 in Scopus for Control and Optimization
Thank you to our editors, reviewers, and authors!
https://t.co/OVpU0mTCCo
#IJUQ #UncertaintyQuantification #AppliedMath
International Journal for Uncertainty Quantification #JCR2026 metrics:
📈 Impact Factor: 1.6
📊 CiteScore: 3.4
🏆 Q1 in Scopus for Control and Optimization
Thank you to our editors, reviewers, and authors!
https://t.co/nh7kp7Uv5L
#IJUQ #UncertaintyQuantification #AppliedMath
💻 Code: https://t.co/tLL1y3NrPn
📄 Preprint: https://t.co/13rhr70KDH
Co-authored w/ @PedroCVieira0 & @pedroribeiro_pt.
#MachineLearning #GraphNeuralNetworks #DeepLearning #UncertaintyQuantification #GeometricDeepLearning
On the SIAM News Blog, Shyam Mohan Subbiah Pillai details his mathematical model that utilizes #StochasticOptimalControl, #NumericalAnalysis, and #UncertaintyQuantification to address issues surrounding renewable energy for cellular networks. Check it out! https://t.co/byFuhVoGHY
Our new review article “Calibration, Sensitivity and Uncertainty Analysis of Complex Ecological Models—A Review” now online and freely available in #EcologyLetters https://t.co/DkM3jz2NVe #Ecology #EcologicalModelling #SensitivityAnalysis #UncertaintyQuantification
Huge thanks to my amazing coauthors: @kuben45, @guipsoares, Thiago Rodrigo Ramos, and Rafael Stern.
Paper: https://t.co/FXnmnT2NEb
#Statistics #MachineLearning #ConformalPrediction #UncertaintyQuantification #AI
But in my study with @plc_rodrigues across 39 datasets they performed really well. In particular, for photometric redshift prediction, TabPFN trained on 50k galaxies beat all baselines trained on 500k. https://t.co/Vwo1UHPwuE
#ML #UncertaintyQuantification #FoundationModels
On the SIAM News blog, Leonidas Gkimisis, Nicole Aretz, Marco Tezzele, Thomas Richter, Peter Benner, and Karen Willcox combine multifidelity #uncertaintyquantification and non-intrusive reduced-order models to accurately predict #icesheet melting. https://t.co/TBqxFutIyy
Uncertainty quantification is an important step in establishing the predictive accuracy of simulation models employed in a broad range of disciplines.
📚https://t.co/Ejrmdwu057
Browse Mathematics: https://t.co/PqlFVAgePc
@TheSIAMNews #UncertaintyQuantification
Thanks to everyone who's supported the project so far!
#MachineLearning #ConformalPrediction #AI #TrustworthyAI #MLBooks #UncertaintyQuantification
At #ICML2025 this week?
Come check out our work on controlled generation, simulation-free latent SDEs, and risk monitoring in test-time adaptation, and chat with the awesome students that made it happen!
#SDE #Diffusion #FlowMatching #TTA #UncertaintyQuantification
This is a new kind of prompt-level safety signal:
✅Statistically calibrated
✅Efficient under budget constraints
✅Model-agnostic & non-adversarial
🧭A step toward proactive LLM safety auditing
📜Paper: https://t.co/ocsEd7bYv4
#LLMsafety #UncertaintyQuantification #AIalignment
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: https://t.co/1aiYd9pWl7
5/5 This work was the result of an amazing collaboration with @zargar_soroush as well as @SantoThies, Willem Waegeman, @abojchevski, and @eyke_hu. Check it out and feel free to reach out if you have any questions! #ConformalPrediction #UncertaintyQuantification #MachineLearning
The 7th edition of the UNSURE Workshop is happening in Daejeon, South Korea!
📅 Deadline: June 25, 2025
🌐 https://t.co/u3Jg85IlJc
🤝 With the UQinMIA Tutorial: https://t.co/eMgIa6OhJN
#MICCAI2025 #ML #MedTech #AIinHealthcare #UncertaintyQuantification #CallForPapers
Just presented at the IV Congreso Colombiano de Estadística, sharing my work on "REACT to NHST" and teaching a minicourse on uncertainty quantification in ML.
Grateful for the warm welcome and great discussions with fellow statisticians!
#UncertaintyQuantification #DataScience
Excited that our work on epistemic uncertainty in conformal prediction has been accepted for an oral presentation at UAI! Huge congratulations to my amazing co-authors!
#MachineLearning #UncertaintyQuantification #ConformalPrediction #UAI2025
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