4 papers
Almost Sure Convergence Analysis of Differentially Private Stochastic Gradient Methods
Amartya Mukherjee, Jun Liu
Differentially private stochastic gradient descent (DP-SGD) has become the standard algorithm for training machine learning models with rigorous privacy guarantees. Despite its wid…
Signal Temporal Logic Planning with Time-Varying Robustness
Yating Yuan, Thanin Quartz, Jun Liu
This letter aims to generate a continuous-time trajectory consisting of piecewise Bézier curves that satisfy signal temporal logic (STL) specifications with piecewise time-varying…
Manifold-Guided Lyapunov Control with Diffusion Models
Amartya Mukherjee, Thanin Quartz, Jun Liu
This paper presents a novel approach to generating stabilizing controllers for a large class of dynamical systems using diffusion models. The core objective is to develop stabilizi…
Denoising Diffusion Restoration Tackles Forward and Inverse Problems for the Laplace Operator
Amartya Mukherjee, Melissa M. Stadt, Lena Podina +2
Diffusion models have emerged as a promising class of generative models that map noisy inputs to realistic images. More recently, they have been employed to generate solutions to p…