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Teo Deveney
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2020 – today
- 2024
- [c1]Jan Stanczuk, Georgios Batzolis, Teo Deveney, Carola-Bibiane Schönlieb:
Diffusion Models Encode the Intrinsic Dimension of Data Manifolds. ICML 2024 - [i5]Simone Appella, Simon R. Arridge, Chris J. Budd, Teo Deveney, Lisa Maria Kreusser:
Equidistribution-based training of Free Knot Splines and ReLU Neural Networks. CoRR abs/2407.02153 (2024) - [i4]James Rowbottom, Georg Maierhofer, Teo Deveney, Katharina Schratz, Pietro Liò, Carola-Bibiane Schönlieb, Chris J. Budd:
G-Adaptive mesh refinement - leveraging graph neural networks and differentiable finite element solvers. CoRR abs/2407.04516 (2024) - 2023
- [j1]Teo Deveney, Eike Hermann Müller, Tony Shardlow:
Deep Surrogate Accelerated Delayed-Acceptance Hamiltonian Monte Carlo for Bayesian Inference of Spatio-Temporal Heat Fluxes in Rotating Disc Systems. SIAM/ASA J. Uncertain. Quantification 11(3): 970-995 (2023) - [i3]Teo Deveney, Jan Stanczuk, Lisa Maria Kreusser, Chris J. Budd, Carola-Bibiane Schönlieb:
Closing the ODE-SDE gap in score-based diffusion models through the Fokker-Planck equation. CoRR abs/2311.15996 (2023) - 2022
- [i2]Teo Deveney, Eike Hermann Müller, Tony Shardlow:
Deep surrogate accelerated delayed-acceptance HMC for Bayesian inference of spatio-temporal heat fluxes in rotating disc systems. CoRR abs/2204.02272 (2022)
2010 – 2019
- 2019
- [i1]Teo Deveney, Eike Hermann Müller, Tony Shardlow:
A deep surrogate approach to efficient Bayesian inversion in PDE and integral equation models. CoRR abs/1910.01547 (2019)
Coauthor Index
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last updated on 2024-09-04 01:20 CEST by the dblp team
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