16 citations · 20 across the 10 of their papers we have counts for
10 papers
SEIS: Subspace-based Equivariance and Invariance Scores for Neural Representations
Huahua Lin, Katayoun Farrahi, Xiaohao Cai
Understanding how neural representations respond to geometric transformations is essential for evaluating whether learned features preserve meaningful spatial structure. Existing a…
SynthFormer: Equivariant Pharmacophore-based Generation of Synthesizable Molecules for Ligand-Based Drug Design
Zygimantas Jocys, Zhanxing Zhu, Henriette M. G. Willems +1
Drug discovery is a complex, resource-intensive process requiring significant time and cost to bring new medicines to patients. Many generative models aim to accelerate drug discov…
Cascade Learning Localises Discriminant Features in Visual Scene Classification
Junwen Wang, Katayoun Farrahi
Lack of interpretability of deep convolutional neural networks (DCNN) is a well-known problem particularly in the medical domain as clinicians want trustworthy automated decisions.…
Improving the Robustness of Neural Multiplication Units with Reversible Stochasticity
Bhumika Mistry, Katayoun Farrahi, Jonathon Hare
Multilayer Perceptrons struggle to learn certain simple arithmetic tasks. Specialist neural modules for arithmetic can outperform classical architectures with gains in extrapolatio…
Data-Driven Interpolation for Super-Scarce X-Ray Computed Tomography
Emilien Valat, Katayoun Farrahi, Thomas Blumensath
We address the problem of reconstructing X-Ray tomographic images from scarce measurements by interpolating missing acquisitions using a self-supervised approach. To do so, we trai…
Modelling nonlinear dependencies in the latent space of inverse scattering
Juliusz Ziomek, Katayoun Farrahi
The problem of inverse scattering proposed by Angles and Mallat in 2018, concerns training a deep neural network to invert the scattering transform applied to an image. After such…
Sinogram Enhancement with Generative Adversarial Networks using Shape Priors
Emilien Valat, Katayoun Farrahi, Thomas Blumensath
Compensating scarce measurements by inferring them from computational models is a way to address ill-posed inverse problems. We tackle Limited Angle Tomography by completing the se…
Learning Division with Neural Arithmetic Logic Modules
Bhumika Mistry, Katayoun Farrahi, Jonathon Hare
To achieve systematic generalisation, it first makes sense to master simple tasks such as arithmetic. Of the four fundamental arithmetic operations (+,-,,), division is…
A Primer for Neural Arithmetic Logic Modules
Bhumika Mistry, Katayoun Farrahi, Jonathon Hare
Neural Arithmetic Logic Modules have become a growing area of interest, though remain a niche field. These modules are neural networks which aim to achieve systematic generalisatio…
Socio-inspired ICT - Towards a socially grounded society-ICT symbiosis
A. Ferscha, K. Farrahi, J. van denHoven +4
Modern ICT (Information and Communication Technology) has developed a vision where the "computer" is no longer associated with the concept of a single device or a network of device…