154 citations · 474 across the 50 of their papers we have counts for
54 papers
Block Disentanglement in CRL: Bridging Identifiability and Visual State Estimation
Emre Acartürk, Pranamya Kulkarni, Puranjay Datta +3
Causal representation learning (CRL) is the process of recovering causally-related latent variables from high-dimensional observations. As a label-free inference method, CRL is par…
Single-Voxel Wireless NeRF for Spatial Spectrum Prediction
Raj Bakhunchhe, Arun Paidimarri, Sara Garcia Sanchez +3
Wireless channel measurements across multiple spatial directions are crucial for AI-driven applications, such as RF digital twins and integrated communication and sensing. However,…
Probability-Maximizing Change Detection: Finite-Window Optimality
Ali Tajer, Javad Heydari
This paper investigates probability-maximizing sequential change detection, a formulation in which performance is measured by the probability of stopping within an admissible inter…
Pollak's Minimax Quickest Change Detection: Non-Asymptotic Optimality
Ali Tajer
Although Pollak's minimax formulation is one of the central frameworks in quickest change detection (QCD), the strongest general optimality results available for it are predominant…
Multi-component Causal Tracing in Large Language Models
Zirui Yan, Dennis Wei, Dmitriy A. Katz +2
Causal tracing systematically intervenes on a large language model's (LLM's) internal representations to uncover and quantify the causal pathways linking specific inputs or computa…
ROPES: Robotic Pose Estimation via Score-Based Causal Representation Learning
Pranamya Kulkarni, Puranjay Datta, Burak Varıcı +3
Causal representation learning (CRL) has emerged as a powerful unsupervised framework that (i) disentangles the latent generative factors underlying high-dimensional data, and (ii)…