9 papers
Amortizing the Calibration Triple: A Projection-Consistent Neural Operator for Local-Stochastic Volatility
Xiaozhen Wang, Anaïs Després, Martin Dureau +1
Local-stochastic volatility (LSV) combines vanilla marginals with richer smile dynamics, but calibration requires a slow, noisy and sequential McKean--Vlasov fixed point. We learn…
Climate-Dyna Deep Hedging for XVAs: Model-Based Reinforcement Learning, Residual Climate HVA, and Hedge-Instrument Discovery
Xiaozhen Wang, Francois Buet-Golfouse
For a trading desk, residual climate hedging valuation adjustment (HVA) is the climate cost left after its inherited hedge and any admissible overlay have been taken into account;…
Generalized specific entropy on Wiener space with application to Martingale Optimal Transport
Francois Buet-Golfouse, Anaïs Després, Zhenjie Ren +1
Classical entropy regularization is poorly suited to continuous-time martingale transport, since relative entropy between diffusion laws typically forces their volatility character…
Generative Transfer for Entropic Optimal Transport with Unknown Costs
Antoine Debouchage, Xiaozhen Wang, Zhenjie Ren +1
This paper addresses the practical challenge in Entropic Optimal Transport (EOT) where the underlying ground cost function is typically latent and unobserved. Rather than assuming…
Sig-DEG for Distillation: Making Diffusion Models Faster and Lighter
Lei Jiang, Wen Ge, Niels Cariou-Kotlarek +7
Diffusion models achieve state-of-the-art generative performance but remain computationally expensive at inference, often requiring many discretization steps. We propose Sig-DEG (S…
Deciding Bank Interest Rates -- A Major-Minor Impulse Control Mean-Field Game Perspective
Fan Chen, Nicholas Martin, Po-Yu Chen +3
Deciding bank interest rates has been a long-standing challenge in finance. It is crucial to ensure that the selected rates balance market share and profitability. However, traditi…
A Comprehensive Sustainable Framework for Machine Learning and Artificial Intelligence
Roberto Pagliari, Peter Hill, Po-Yu Chen +3
In financial applications, regulations or best practices often lead to specific requirements in machine learning relating to four key pillars: fairness, privacy, interpretability a…
Differentially Private Fine-Tuning of Diffusion Models
Yu-Lin Tsai, Yizhe Li, Zekai Chen +4
The integration of Differential Privacy (DP) with diffusion models (DMs) presents a promising yet challenging frontier, particularly due to the substantial memorization capabilitie…
Online Personalizing White-box LLMs Generation with Neural Bandits
Zekai Chen, Weeden Daniel, Po-yu Chen +1
The advent of personalized content generation by LLMs presents a novel challenge: how to efficiently adapt text to meet individual preferences without the unsustainable demand of c…