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cs.LG2025
Bhargava Cube--Inspired Quadratic Regularization for Structured Neural Embeddings
S Sairam, Prateek P Kulkarni
We present a novel approach to neural representation learning that incorporates algebraic constraints inspired by Bhargava cubes from number theory. Traditional deep learning metho…
cs.LG2025
The Final-Stage Bottleneck: A Systematic Dissection of the R-Learner for Network Causal Inference
S Sairam, Sara Girdhar, Shivam Soni
The R-Learner is a powerful, theoretically-grounded framework for estimating heterogeneous treatment effects, prized for its robustness to nuisance model errors. However, its appli…