fismedMedical Physics,
AI and Neurotechnology
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Medical Physics, AI and Neurotechnology · University of Rome Tor Vergata

fismed@uniroma2.it

FISMED / LABORATORIES

AI and Neural Decoding

Machine learning methods connect images, language and sound with neural recordings and other complex data. Research combines generative models, representation learning and multimodal alignment to develop neural encoding and decoding. Graph and geometric learning, model interpretability and uncertainty quantification support robust analysis across datasets, participants and recording modalities.

02 / LABORATORY

AI and Neural Decoding

Machine learning methods connect images, language and sound with neural recordings and other complex data. Research combines generative models, representation learning and multimodal alignment to develop neural encoding and decoding. Graph and geometric learning, model interpretability and uncertainty quantification support robust analysis across datasets, participants and recording modalities.

  • Neural encoding and decoding
  • Generative and multimodal learning
  • Graph and geometric deep learning
  • Interpretability and uncertainty quantification
AI and neural decodingNetworks and dynamics
Explore related research

Connections indicate shared research topics, not authorship or project participation.

Neural encoding · Neural decoding · Generative model · Machine learning · Deep learning

Machine learning methods connect images, language and sound with neural recordings and other complex data. Research combines generative models, representation learning and multimodal alignment to develop neural encoding and decoding. Graph and geometric learning, model interpretability and uncertainty quantification support robust analysis across datasets, participants and recording modalities.