1 citations · 1 across the 6 of their papers we have counts for
6 papers
ViTaPEs: Visuotactile Position Encodings for Cross-Modal Alignment in Multimodal Transformers
Fotios Lygerakis, Ozan Özdenizci, Elmar Rückert
Tactile sensing provides local essential information that is complementary to visual perception, such as texture, compliance, and force. Despite recent advances in visuotactile rep…
ED-VAE: Entropy Decomposition of ELBO in Variational Autoencoders
Fotios Lygerakis, Elmar Rueckert
Traditional Variational Autoencoders (VAEs) are constrained by the limitations of the Evidence Lower Bound (ELBO) formulation, particularly when utilizing simplistic, non-analytic,…
Multimodal Visual-Tactile Representation Learning through Self-Supervised Contrastive Pre-Training
Vedant Dave, Fotios Lygerakis, Elmar Rueckert
The rapidly evolving field of robotics necessitates methods that can facilitate the fusion of multiple modalities. Specifically, when it comes to interacting with tangible objects,…
M2CURL: Sample-Efficient Multimodal Reinforcement Learning via Self-Supervised Representation Learning for Robotic Manipulation
Fotios Lygerakis, Vedant Dave, Elmar Rueckert
One of the most critical aspects of multimodal Reinforcement Learning (RL) is the effective integration of different observation modalities. Having robust and accurate representati…
CR-VAE: Contrastive Regularization on Variational Autoencoders for Preventing Posterior Collapse
Fotios Lygerakis, Elmar Rueckert
The Variational Autoencoder (VAE) is known to suffer from the phenomenon of \textit{posterior collapse}, where the latent representations generated by the model become independent…
Sequential Late Fusion Technique for Multi-modal Sentiment Analysis
Debapriya Banerjee, Fotios Lygerakis, Fillia Makedon
Multi-modal sentiment analysis plays an important role for providing better interactive experiences to users. Each modality in multi-modal data can provide different viewpoints or…