3 citations · 5 across the 20 of their papers we have counts for
4 papers · 1 filter
Disentanglement with Holographic Reduced Representations
Jhonny J. Velasquez Olivera, Christo K. Thomas, Walid Saad
Disentanglement, the separation of factors of variation in data using neural networks, remains a long-standing challenge in machine learning. Prior work has addressed this problem…
Toward World Models for Epidemiology
Zeeshan Memon, Yiqi Su, Christo Kurisummoottil Thomas +3
World models have emerged as a unifying paradigm for learning latent dynamics, simulating counterfactual futures, and supporting planning under uncertainty. In this paper, we argue…
Causal Semantic Communication for Digital Twins: A Generalizable Imitation Learning Approach
Christo Kurisummoottil Thomas, Walid Saad, Yong Xiao
A digital twin (DT) leverages a virtual representation of the physical world, along with communication (e.g., 6G), computing (e.g., edge computing), and artificial intelligence (AI…
Neuro-Symbolic Causal Reasoning Meets Signaling Game for Emergent Semantic Communications
Christo Kurisummoottil Thomas, Walid Saad
Semantic communication (SC) aims to communicate reliably with minimal data transfer while simultaneously providing seamless connectivity to heterogeneous services and users. In thi…