2023
- October 2023: Interested in Stochastic Gradient Descent on functional data? Have a look at our new JMLR article! (with Kexin Jin, Chenguang Liu, Carola-Bibiane Schönlieb)
- October 2023: New preprint on nested sampling, uncertainty quantification, and rare event estimation by Doris Schneider, Philipp Wacker, and myself.
- September 2023: I joined the Department of Mathematics at the University of Manchester as a Lecturer in Applied Mathematics.
- August 2023: I was fortunate enough to win a SIGEST Award for my article “On the Well-posedness of Bayesian Inverse Problems” [L. 2020; SIAM/ASA J. Uncertain. Quantif. 8(1), p. 451–482]. Thus, an updated version of this article titled “Bayesian Inverse Problems are Usually Well-posed” has just appeared in SIAM Review [L. 2023; SIAM Rev. 65(3), p. 831-865].
- July 2023: Matei Hanu, Claudia Schillings, and I have published an article on Subsampling in Ensemble Kalman Inversion. Here is an open access link.
- June 2023: Our article on Joint Reconstruction-Segmentation on Graphs just appeared in the SIAM Journal on Imaging Sciences! Here is a link.
- May 2023: Kexin Jin, Chenguang Liu, and I are wondering how data subsampling influences Langevin-based MCMC algorithms — of course, we consider the continuous-time case. Here is a preprint on the Subsampling error in Stochastic Gradient Langevin Diffusions.
- May 2023: We had an amazing INI/ICMS workshop on the Mathematical Foundations of Data-driven Engineering this week. You can find the programme here and the group photo here.
- May 2023: The contributions that were part of the Mathematics Showdown are now available on Youtube. Link to the playlist.
- April 2023: Jonna Roden and I organised the ‘Mathematics Showdown’ – an Edinburgh Science Festival event consisting of five highly engaging talks by Mathematics PhD students from the Maxwell Institute Graduate School. What a great evening! (tweet with photo)
- February 2023: New preprint by Matei Hanu, Claudia Schillings, and myself: Subsampling in ensemble Kalman inversion.
- February 2023: I am co-organising a workshop on Mathematical Foundations of Data-Driven Engineering at the ICMS, Edinburgh. Applications open!
- February 2023: Tamara Grossmann, Julia Komorowska, Carola-Bibiane Schönlieb and I have submitted a new preprint: Can Physics-Informed Neural Networks beat the Finite Element Method?
2022
- November 2022: My article Gradient flows and randomised thresholding: sparse inversion and classification was published in Inverse Problems‘ special issue Emerging Talents 2021.
- September 2022: Kexin Jin, Chenguang Liu, Alessandro Scagliotti, and I submitted a new preprint: Losing momentum in continuous-time stochastic optimisation.
- September 2022: Björn Sprungk and I published an outreach article on Bayesian inverse problems as a Snapshot of Modern Mathematics from Oberwolfach.
- August 2022: Jeremy Budd, Yves van Gennip, Simone Parisotto, Carola-Bibiane Schönlieb, and I submitted a new preprint: Joint reconstruction-segmentation on graphs.
- March 2022: New preprint: Gradient flows and randomised thresholding: sparse inversion and classification.
- March 2022: Yury Korolev, Carola-Bibiane Schönlieb, and I submitted a new preprint: Gaussian random fields on non-separable Banach spaces.
- February 2022: I gave a talk in Oberwolfach on stochastic gradient descent in continuous time.
2021
- December 2021: Kexin Jin, Chenguang Liu, Carola-Bibiane Schönlieb, and I submitted a new preprint: A Continuous-time Stochastic Gradient Descent Method for Continuous Data.
- September 2021: Simon Urbainczyk joined Heriot-Watt University as a PhD student. He will be supervised jointly by Aretha Teckentrup, University of Edinburgh, and myself.
- September 2021: I joined Heriot-Watt University as an Assistant Professor.
- August 2021: Our article Generalized parallel tempering on Bayesian inverse problems appeared in Statistics and Computing.