5 papers
Learned Graph Bases for Neural Operators on Power-System Transients
Shubhan Bhattacharya, Avi Bagchi
Fourier neural operators predict power-system transient trajectories with high accuracy. We extend this line of work by examining the choice of spatial spectral basis, studying bot…
ALF: Spectrally Anchored Latent Flow Matching for Wireless Signal Generation
Yiyang Li, Sai Shankar Narasimhan, Priam Alataris +3
Wireless time-series generation is useful for emerging applications that will drive the adoption and integration of machine learning tasks within next-generation networks, such as…
Factor Dimensionality and the Bias-Variance Tradeoff in Diffusion Portfolio Models
Avi Bagchi, Michael Tesfaye, Om Shastri
In this paper, we implement and evaluate a conditional diffusion model for asset return prediction and portfolio construction on large-scale equity data. Our method models the full…
Doppler Invariant CNN for Signal Classification
Avi Bagchi, Dwight Hutchenson
Radio spectrum monitoring in contested environments motivates the need for reliable automatic signal classification technology. Prior work highlights deep learning as a promising a…
Watermarking Discrete Diffusion Language Models
Avi Bagchi, Akhil Bhimaraju, Moulik Choraria +2
Watermarking has emerged as a promising technique to track AI-generated content and differentiate it from authentic human creations. While prior work extensively studies watermarki…