Portfolio Optimization Proxies under Label Scarcity and Regime Shifts — Bayesian and Deterministic Students under Semi-Supervised Sandwich Training

By Adhiraj Chattopadhyaya

Published 2026-04-04

Everscope rating

1585.4

Relevance to quantitative trading

9 / 10

Implementation complexity

7 / 10

Reproducibility

3 / 5

About this paper

Methodology: Semi-Supervised Sandwich Training with Bayesian Knowledge Distillation. Problem types: Portfolio Optimization, Risk Management, Semi-supervised Learning, Transfer Learning, Optimization, Generative Modeling (synthetic data).

arXiv:2604.14206 · Paper rankings

Open the interactive Everscope explorer for full analysis, charts, and paper battles.