3 citations · 3 across the 6 of their papers we have counts for
6 papers
Latent-LoRA: Compact Latent-Space Adapters with Gradient-Free Routing for Continual Learning
Reza Rahimi Azghan, Gautham Krishna Gudur, Giulia Pedrielli +2
Large language models generalize well to individual tasks but lack an inherent mechanism for learning them sequentially, leading to catastrophic forgetting. To mitigate this, LoRA-…
Gated Adaptation for Continual Learning in Human Activity Recognition
Reza Rahimi Azghan, Gautham Krishna Gudur, Mohit Malu +4
Wearable sensors in Internet of Things (IoT) ecosystems increasingly support applications such as remote health monitoring, elderly care, and smart home automation, all of which re…
GluMind: Multimodal Parallel Attention and Knowledge Retention for Robust Cross-Population Blood Glucose Forecasting
Ebrahim Farahmand, Reza Rahimi Azghan, Nooshin Taheri Chatrudi +9
This paper proposes GluMind, a transformer-based multimodal framework designed for continual and long-term blood glucose forecasting. GluMind devises two attention mechanisms, incl…
CLAD-Net: Continual Activity Recognition in Multi-Sensor Wearable Systems
Reza Rahimi Azghan, Gautham Krishna Gudur, Mohit Malu +4
The rise of deep learning has greatly advanced human behavior monitoring using wearable sensors, particularly human activity recognition (HAR). While deep models have been widely s…
Guiding Diffusion with Deep Geometric Moments: Balancing Fidelity and Variation
Sangmin Jung, Utkarsh Nath, Yezhou Yang +5
Text-to-image generation models have achieved remarkable capabilities in synthesizing images, but often struggle to provide fine-grained control over the output. Existing guidance…
AttenGluco: Multimodal Transformer-Based Blood Glucose Forecasting on AI-READI Dataset
Ebrahim Farahmand, Reza Rahimi Azghan, Nooshin Taheri Chatrudi +6
Diabetes is a chronic metabolic disorder characterized by persistently high blood glucose levels (BGLs), leading to severe complications such as cardiovascular disease, neuropathy,…