@misc{rezvani2025interpretableeegtoimagegenerationsemantic,title={Interpretable EEG-to-Image Generation with Semantic Prompts},author={Rezvani, Arshak and Akbari, Ali and Arani, Kosar Sanjar and Mirian, Maryam and Arasteh, Emad and McKeown, Martin J.},year={2025},journal={Actionable Interpretability Workshop at International Conference on Machine Learning},archiveprefix={arXiv},primaryclass={cs.CV},url={https://arxiv.org/abs/2507.07157},equal_contribution={Arshak Rezvani and Ali Akbari},}
IEEE
DiffuseGaitNet: Improving Parkinson’s Disease Gait Severity Assessment With a Diffusion Model Framework
Arshak Rezvani, Nasrin Ravansalar, Mohammad Ali Akhaee, and 5 more authors
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2025
@article{11080070,author={Rezvani, Arshak and Ravansalar, Nasrin and Akhaee, Mohammad Ali and Greenshaw, Andrew J. and Greiner, Russell and Mirian, Maryam S. and Yousefnezhad, Muhammad and McKeown, Martin J.},journal={IEEE Transactions on Neural Systems and Rehabilitation Engineering},title={DiffuseGaitNet: Improving Parkinson’s Disease Gait Severity Assessment With a Diffusion Model Framework},year={2025},volume={33},number={},pages={2858-2869},keywords={Diffusion models;Diseases;Data models;Feature extraction;Transformers;Three-dimensional displays;Noise;Uncertainty;Training;Predictive models;Diffusion models;generative AI;transformers;attention-based networks;Parkinson’s disease;gait impairments;human action recognition;MDS-UPDRS},doi={10.1109/TNSRE.2025.3589074},}