no code implementations • 21 Nov 2023 • Junwen Wang, Katayoun Farrahi
In this work, we investigate the localisation of features learned via two varied learning paradigms and demonstrate the superiority of one learning approach with respect to localisation.
no code implementations • 10 Nov 2022 • Bhumika Mistry, Katayoun Farrahi, Jonathon Hare
Multilayer Perceptrons struggle to learn certain simple arithmetic tasks.
no code implementations • 16 May 2022 • Emilien Valat, Katayoun Farrahi, Thomas Blumensath
To do so, we train shallow neural networks to combine two neighbouring acquisitions into an estimated measurement at an intermediate angle.
no code implementations • 19 Mar 2022 • Juliusz Ziomek, Katayoun Farrahi
The conducted meta-analysis also shows a clear practical advantage of such constructed generative models in terms of the efficiency of their training process compared to existing generative models for images.
no code implementations • 1 Feb 2022 • Emilien Valat, Katayoun Farrahi, Thomas Blumensath
Compensating scarce measurements by inferring them from computational models is a way to address ill-posed inverse problems.
1 code implementation • NeurIPS 2021 • Bhumika Mistry, Katayoun Farrahi, Jonathon Hare
To achieve systematic generalisation, it first makes sense to master simple tasks such as arithmetic.
2 code implementations • 23 Jan 2021 • Bhumika Mistry, Katayoun Farrahi, Jonathon Hare
Neural Arithmetic Logic Modules have become a growing area of interest, though remain a niche field.