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  • Currently displaying 21 - 40 of 336 publications
HAMLET: Graph Transformer Neural Operator for Partial Differential Equations
A Bryutkin, J Huang, Z Deng, G Yang, C-B Schönlieb, A Aviles-Rivero
(2024)
(link to publication)
LLMs learn governing principles of dynamical systems, revealing an in-context neural scaling law
TJB Liu, N Boullé, R Sarfati, CJ Earls
(2024)
(link to publication)
Operator learning without the adjoint
N Boullé, D Halikias, SE Otto, A Townsend
(2024)
(link to publication)
On the Convergence of Hermitian Dynamic Mode Decomposition
N Boullé, MJ Colbrook
(2024)
(doi: 10.48550/arxiv.2401.03192)
A mathematical guide to operator learning
N Boullé, A Townsend
– Handbook of Numerical Analysis
(2024)
25,
83
(doi: 10.1016/bs.hna.2024.05.003)
Modeling of a Liquid Leaf Target TNSA Experiment Using Particle-In-Cell Simulations and Deep Learning
B Schmitz, D Kreuter, O Boine-Frankenheim
– Laser and Particle Beams
(2024)
2023,
e3
(doi: 10.1155/2023/2868112)
A Mathematical Guide to Operator Learning
N Boullé, A Townsend
(2023)
(link to publication)
Deep Gaussian Process Priors for Bayesian Inference in Nonlinear Inverse Problems
K Abraham, N Deo
(2023)
(link to publication)
Multivariate rational approximation of functions with curves of singularities
N Boullé, A Herremans, D Huybrechs
(2023)
(link to publication)
The curious case of the test set AUROC
M Roberts, A Hazan, S Dittmer, JHF Rudd, C-B Schönlieb
(2023)
(doi: 10.48550/arxiv.2312.16188)
Dynamical Systems–Based Neural Networks
E Celledoni, D Murari, B Owren, CB Schonlieb, F Sherry
– SIAM Journal on Scientific Computing
(2023)
45,
a3071
(doi: 10.1137/22m1527337)
Single-Shot Plug-and-Play Methods for Inverse Problems
Y Cheng, L Zhang, Z Shen, S Wang, L Yu, RH Chan, C-B Schönlieb, AI Aviles-Rivero
(2023)
(link to publication)
TRIDENT: The Nonlinear Trilogy for Implicit Neural Representations
Z Shen, Y Cheng, RH Chan, P Liò, C-B Schönlieb, AI Aviles-Rivero
(2023)
(link to publication)
Contrastive Registration for Unsupervised Medical Image Segmentation
L Liu, AI Aviles-Rivero, C-B Schonlieb
– IEEE Trans Neural Netw Learn Syst
(2023)
PP,
1
(doi: 10.1109/tnnls.2023.3332003)
Traffic Video Object Detection using Motion Prior
L Liu, Y Cheng, D Chen, J He, P Liò, C-B Schönlieb, AI Aviles-Rivero
(2023)
(link to publication)
Contractive Systems Improve Graph Neural Networks Against Adversarial Attacks
M Eliasof, D Murari, F Sherry, C-B Schönlieb
(2023)
(link to publication)
Multi-Modal Learning for Predicting the Genotype of Glioma.
Y Wei, X Chen, L Zhu, L Zhang, C-B Schonlieb, S Price, C Li
– IEEE Trans Med Imaging
(2023)
42,
3167
(doi: 10.1109/TMI.2023.3244038)
Recent Methodological Advances in Federated Learning for Healthcare
F Zhang, D Kreuter, Y Chen, S Dittmer, S Tull, T Shadbahr, B Collaboration, J Preller, JHF Rudd, JAD Aston, C-B Schönlieb, N Gleadall, M Roberts
(2023)
(doi: 10.48550/arxiv.2310.02874)
Adaptive mixed FEM combined with the method of characteristics for stationary convection–diffusion–reaction problems
MC Antony Oliver, M González
– Finite Elements in Analysis and Design
(2023)
227,
104045
(doi: 10.1016/j.finel.2023.104045)
Elliptic PDE learning is provably data-efficient.
N Boullé, D Halikias, A Townsend
– Proceedings of the National Academy of Sciences of the United States of America
(2023)
120,
e2303904120
(doi: 10.1073/pnas.2303904120)

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