4 papers · 1 filter
Posterior-Calibrated Causal Circuits in Variational Autoencoders: Why Image-Domain Interpretability Fails on Tabular Data
Dip Roy, Rajiv Misra, Sanjay Kumar Singh +1
Although mechanism-based interpretability has generated an abundance of insight for discriminative network analysis, generative models are less understood -- particularly outside o…
A Multi-Level Causal Intervention Framework for Mechanistic Interpretability in Variational Autoencoders
Dip Roy, Rajiv Misra, Sanjay Kumar Singh +1
Understanding how generative models represent and transform data is a foundational problem in deep learning interpretability. While mechanistic interpretability of discriminative a…
Fundamental Limits of Neural Network Sparsification: Evidence from Catastrophic Interpretability Collapse
Dip Roy, Rajiv Misra, Sanjay Kumar Singh
Extreme neural network sparsification (90% activation reduction) presents a critical challenge for mechanistic interpretability: understanding whether interpretable features surviv…
ARDDQN: Attention Recurrent Double Deep Q-Network for UAV Coverage Path Planning and Data Harvesting
Praveen Kumar, Priyadarshni, Rajiv Misra
Unmanned Aerial Vehicles (UAVs) have gained popularity in data harvesting (DH) and coverage path planning (CPP) to survey a given area efficiently and collect data from aerial pers…