Search Results for author:
Found 6 papers, 1 papers with code
Tomography of Quantum States from Structured Measurements via quantum-aware transformer
Quantum state tomography (QST) is the process of reconstructing the state of a quantum system (mathematically described as a density matrix) through a series of different measurements, which can be solved by learning a parameterized function to translate experimentally measured statistics into physical density matrices.
Uncertainty Quantification by Random Measures and Fields
The first and second order global sensitivity analyses conveyed through random counting measures elucidate and integrate different notions of uncertainty quantification, and the global sensitivity analysis of random fields conveys the proportionate functional contributions to covariance.
Model Selection
Probability
Methodology
60G57, 60G60, 60G55
Multi-Level Evolution Strategies for High-Resolution Black-Box Control
Such problems arise in engineering and scientific applications, which possess a multi-resolution control nature, and thus may be formulated either by means of low-resolution variants (providing coarser approximations with presumably lower accuracy for the general problem) or by high-resolution controls.
Targeted Nonlinear Adversarial Perturbations in Images and Videos
We introduce a method for learning adversarial perturbations targeted to individual images or videos.
High Dimensional Model Representation as a Glass Box in Supervised Machine Learning
Explanation provides the necessary and sufficient information to interpret the model output in terms of the model input.
Learning-based Quantum Robust Control: Algorithm, Applications and Experiments
Numerical results are presented to demonstrate the excellent performance of the improved machine learning algorithm for these two classes of quantum robust control problems.
