paper-conference

It has been observed that representations learned by distinct neural networks conceal structural similarities when the models are …

Models trained on semantically related datasets and tasks exhibit comparable inter-sample relations within their latent spaces. We …

CLIP proved that aligning visual and language spaces is key to solving many vision tasks without explicit training, but required to …

Different neural models often exhibit similar latent spaces when exposed to semantically similar data; however, this inherent …

Neural networks embed the geometric structure of a data manifold lying in a high-dimensional space into latent representations. …

Few-shot graph classification is a novel yet promising emerging research field that still lacks the soundness of well-established …

In this paper, we propose a transformer-based procedure for the efficient registration of non-rigid 3D point clouds. The proposed …

The paper investigates if and how the topology of the peer-assessment network can affect the performance of the Bayesian model adopted …

The paper presents a study of the performance variations of the Bayesian model of peer-assessment implemented in OpenAnswer, in terms …