New Preprint: "A Quantum Spectral Method for Non-Periodic Boundary Value Problems", by @ekyvalens, Yiren Wang, @BurigedeL , Michael Ortiz and @fehmiCirak
https://t.co/WrYGaXsWLI
⚡️Preprint alert: “Multi-view Bayesian optimisation in reduced dimension for engineering design” by Thomas Archbold, @IevaKazlauskai, @fehmiCirak
https://t.co/YPx7fyXsJb
New Preprint: "A Quantum Spectral Method for Non-Periodic Boundary Value Problems", by @ekyvalens, Yiren Wang, @BurigedeL , Michael Ortiz and @fehmiCirak
https://t.co/WrYGaXsWLI
Excited to welcome @YaswanthSai to the team as a postdoc!
Yaswanth joins us from the University of Illinois Urbana-Champaign and will be focusing on Bayesian inference and PDEs with uncertain/imperfect boundaries.
I am looking forward to attending ADMOS 2025 next week and giving a plenary lecture on
"Learning from uncertain models and limited data for digital design and twinning."
https://t.co/tjCuxtQ7SL
Please apply or share: Research Assistant/Associate in Computational Mechanics at University of Cambridge, focusing on computational methods for uncertain/imperfect geometries. Join our team!
https://t.co/p5uLXSYgGe
If you happen to be in Cambridge, don't miss Arnaud's seminar on Population-Based Inference in Mechanics.
Friday 07 February 2025, 15:00-16:00
https://t.co/xofbciz0TQ
⚡️Preprint alert: “Multi-view Bayesian optimisation in reduced dimension for engineering design” by Thomas Archbold, @IevaKazlauskai, @fehmiCirak
https://t.co/YPx7fyXsJb
📜Preprint alert: "Mechanical State Estimation with a Polynomial-Chaos-Based Statistical Finite Element Method". An exciting collaboration with our esteemed colleagues at TU Braunschweig!
https://t.co/oEnpVC3v3E|
📣 New paper 📣
Variational Bayesian surrogate modelling with application to robust design optimisation
Thomas Archbold, @IevaKazlauskai, @fehmiCirak
Computer Methods in Applied Mechanics and Engineering (2024)
https://t.co/EKGjIi2Z5A
Can quantum computing revolutionize computational mechanics? We introduce a PDE solver that achieves exponential speedup, reducing complexity from O(Nᶜ) to O((log N)ᶜ).
🔗 https://t.co/QV10BT9HGc
Paper by @BurigedeL, Michael Ortiz, and @fehmiCirak, recently accepted in CMAME.