From the 1 of 6 linked papers with an AI index.
6 papers
The log log jam in Gaussian state tomography
Sitan Chen, Weiyuan Gong, Qi Ye +1
The paper proves that any tomography protocol using Gaussian measurements on continuous‑variable systems inevitably incurs a sample complexity that scales as log log E with the sys…
Computation-Utility-Privacy Tradeoffs in Bayesian Estimation
Sitan Chen, Jingqiu Ding, Mahbod Majid +1
Bayesian methods lie at the heart of modern data science and provide a powerful scaffolding for estimation in data-constrained settings and principled quantification and propagatio…
Optimal Inference Schedules for Masked Diffusion Models
Sitan Chen, Kevin Cong, Jerry Li
A major bottleneck of standard auto-regressive large language models is that their inference process is inherently sequential, resulting in very long and costly inference times. To…
S4S: Solving for a Diffusion Model Solver
Eric Frankel, Sitan Chen, Jerry Li +3
Diffusion models (DMs) create samples from a data distribution by starting from random noise and iteratively solving a reverse-time ordinary differential equation (ODE). Because ea…
Adaptivity can help exponentially for shadow tomography
Sitan Chen, Weiyuan Gong, Zhihan Zhang
In recent years there has been significant interest in understanding the statistical complexity of learning from quantum data under the constraint that one can only make unentangle…
Stabilizer bootstrapping: A recipe for efficient agnostic tomography and magic estimation
Sitan Chen, Weiyuan Gong, Qi Ye +1
We study the task of agnostic tomography: given copies of an unknown -qubit state which has fidelity with some state in a given class , find a state which has fidel…