35 citations · 55 across the 9 of their papers we have counts for
9 papers
Ansatz-free Hamiltonian learning with Heisenberg-limited scaling
Hong-Ye Hu, Muzhou Ma, Weiyuan Gong +4
Learning the unknown interactions that govern a quantum system is crucial for quantum information processing, device benchmarking, and quantum sensing. The problem, known as Hamilt…
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…
Quantum-Classical Separations in Shallow-Circuit-Based Learning with and without Noises
Zhihan Zhang, Weiyuan Gong, Weikang Li +1
We study quantum-classical separations between classical and quantum supervised learning models based on constant depth (i.e., shallow) circuits, in scenarios with and without nois…
Complexity of Digital Quantum Simulation in the Low-Energy Subspace: Applications and a Lower Bound
Weiyuan Gong, Shuo Zhou, Tongyang Li
Digital quantum simulation has broad applications in approximating unitary evolution of Hamiltonians. In practice, many simulation tasks for quantum systems focus on quantum states…
Robustness of Quantum Algorithms for Nonconvex Optimization
Weiyuan Gong, Chenyi Zhang, Tongyang Li
Recent results suggest that quantum computers possess the potential to speed up nonconvex optimization problems. However, a crucial factor for the implementation of quantum optimiz…
Enhancing Quantum Adversarial Robustness by Randomized Encodings
Weiyuan Gong, Dong Yuan, Weikang Li +1
The interplay between quantum physics and machine learning gives rise to the emergent frontier of quantum machine learning, where advanced quantum learning models may outperform th…
Learning Distributions over Quantum Measurement Outcomes
Weiyuan Gong, Scott Aaronson
Shadow tomography for quantum states provides a sample efficient approach for predicting the properties of quantum systems when the properties are restricted to expectation values…
Weighted Quantum Channel Compiling through Proximal Policy Optimization
Weiyuan Gong, Si Jiang, Dong-Ling Deng
We propose a general and systematic strategy to compile arbitrary quantum channels without using ancillary qubits, based on proximal policy optimization -- a powerful deep reinforc…
Universal Adversarial Examples and Perturbations for Quantum Classifiers
Weiyuan Gong, Dong-Ling Deng
Quantum machine learning explores the interplay between machine learning and quantum physics, which may lead to unprecedented perspectives for both fields. In fact, recent works ha…