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1. Probablistic-modelling-of-features Probablistic-modelling-of-features Public

   This project explores the geometry and probabilistic structure of deep neural network feature spaces, with a focus on class separability, representation collapse, and robustness under adversarial p…

   Jupyter Notebook

2. SLM-based-QA SLM-based-QA Public

   A Flask-based PDF question answering chatbot that compares direct prompting vs retrieval-augmented generation using Supermemory across multiple small and large language models.

   HTML

3. Detecting-Silent-Data-Corruptions-in-Deep-Neural-Networks Detecting-Silent-Data-Corruptions-in-Deep-Neural-Networks Public

   A PyTorch-based implementation of DrDNA, a post-hoc framework for detecting and mitigating soft errors (SDCs) in deep neural networks. The project profiles layer-wise activation statistics and comp…

   Jupyter Notebook

4. Reasoning-of-LLM Reasoning-of-LLM Public

5. MPSLab-ASU/Seperating_OOD_and_ADV MPSLab-ASU/Seperating_OOD_and_ADV Public

   A lightweight PyTorch framework for distinguishing out-of-distribution (OOD) inputs from adversarial (ADV) samples using intermediate feature representations.

   Python