3 papers
cs.LG2026
Is Grokking a Loss of Normal Hyperbolicity of the Interpolation Manifold?
Suvinava Basak
A recent line of work recasts the post-memorization phase of grokking as constrained optimization: once a network interpolates the training set, weight decay drives a slow drift al…
cs.LG2026
ZC-Swish: Stabilizing Deep BN-Free Networks for Edge and Micro-Batch Applications
Suvinava Basak
Batch Normalization (BN) is a cornerstone of deep learning, yet it fundamentally breaks down in micro-batch regimes (e.g., 3D medical imaging) and non-IID Federated Learning. Remov…
cs.CL2026
From Literature to Hypotheses: An AI Co-Scientist System for Biomarker-Guided Drug Combination Hypothesis Generation
Raneen Younis, Suvinava Basak, Lukas Chavez +1
The rapid growth of biomedical literature and curated databases has made it increasingly difficult for researchers to systematically connect biomarker mechanisms to actionable drug…