50 citations · 92 across the 40 of their papers we have counts for
5 papers · 1 filter
CoDeFont: One-Shot Font Generation via Multi-Scale Factor-Specific Representation Learning
Rejoy Chakraborty, Prasun Roy, Saumik Bhattacharya +1
One-shot Font Generation (OFG) aims to synthesize a target glyph by transferring the stylistic characteristics of a single reference glyph while preserving the structure of the tar…
A Path Integral Surrogate for Multi-Step Gradient Inversion in Federated Learning
Agnivo Ghosh, Saumik Bhattacharya
Federated learning lets many clients train a shared model together without ever sending their private data to a central server. Each client shares only a model update, and this upd…
On the Role of the Projector in Contrastive Self-Supervised Learning: Last-Layer Rank Dynamics Drive Representation Quality
Siladittya Manna, Priyangshu Mandal, Umapada Pal +1
The dimensional collapse of representations in self-supervised contrastive learning is an ever-present issue. One notable technique to prevent such a collapse of representations is…
Teacher Knows It Best: Spontaneous Symmetry Breaking and Tipping Points in Networked Langevin Dynamics AI Sycophancy
Sayantari Ghosh, Saumik Bhattacharya, Partha Pratim Chakrabarti
We formulate a statistical physics framework to model a networked stochastic dynamical system exhibiting bistability, driven by additive noise and social conformity. We apply this…
DRG-Font: Dynamic Reference-Guided Few-shot Font Generation via Contrastive Style-Content Disentanglement
Rejoy Chakraborty, Prasun Roy, Saumik Bhattacharya +1
Few-shot Font Generation aims to generate stylistically consistent glyphs from a few reference glyphs. However, capturing complex font styles from a few exemplars remains challengi…