1 citations · 2 across the 10 of their papers we have counts for
4 papers · 1 filter
Manifold Learning Benefits GANs
Yao Ni, Piotr Koniusz, Richard Hartley +1
In this paper, we improve Generative Adversarial Networks by incorporating a manifold learning step into the discriminator. We consider locality-constrained linear and subspace-bas…
Meta-Learning for Multi-Label Few-Shot Classification
Christian Simon, Piotr Koniusz, Mehrtash Harandi
Even with the luxury of having abundant data, multi-label classification is widely known to be a challenging task to address. This work targets the problem of multi-label meta-lear…
Towards a Robust Differentiable Architecture Search under Label Noise
Christian Simon, Piotr Koniusz, Lars Petersson +2
Neural Architecture Search (NAS) is the game changer in designing robust neural architectures. Architectures designed by NAS outperform or compete with the best manual network desi…
On Learning the Geodesic Path for Incremental Learning
Christian Simon, Piotr Koniusz, Mehrtash Harandi
Neural networks notoriously suffer from the problem of catastrophic forgetting, the phenomenon of forgetting the past knowledge when acquiring new knowledge. Overcoming catastrophi…