8 citations · 10 across the 7 of their papers we have counts for
6 papers · 1 filter
SEMASIA: A Large-Scale Dataset of Semantically Structured Latent Representations
Mario Edoardo Pandolfo, Enrico Grimaldi, Lorenzo Marinucci +4
Latent representations learned by neural networks often exhibit semantic structure, where concept similarity is reflected by geometric proximity in embedding space. However, compar…
Semantic Channel Equalization Strategies for Deep Joint Source-Channel Coding
Lorenzo Pannacci, Simone Fiorellino, Mario Edoardo Pandolfo +2
Deep joint source-channel coding (DeepJSCC) has emerged as a powerful paradigm for end-to-end semantic communications, jointly learning to compress and protect task-relevant featur…
Latent Space Alignment for AI-Native MIMO Semantic Communications
Mario Edoardo Pandolfo, Simone Fiorellino, Emilio Calvanese Strinati +1
Semantic communications focus on prioritizing the understanding of the meaning behind transmitted data and ensuring the successful completion of tasks that motivate the exchange of…
RIS-aided Latent Space Alignment for Semantic Channel Equalization
Tomás Hüttebräucker, Mario Edoardo Pandolfo, Simone Fiorellino +2
Semantic communication systems introduce a new paradigm in wireless communications, focusing on transmitting the intended meaning rather than ensuring strict bit-level accuracy. Th…
Relative Representations of Latent Spaces enable Efficient Semantic Channel Equalization
Tomás Hüttebräucker, Simone Fiorellino, Mohamed Sana +2
In multi-user semantic communication, language mismatche poses a significant challenge when independently trained agents interact. We present a novel semantic equalization algorith…
ICML 2023 Topological Deep Learning Challenge : Design and Results
Mathilde Papillon, Mustafa Hajij, Helen Jenne +53
This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning. The competi…