92 citations · 240 across the 12 of their papers we have counts for
4 papers · 1 filter
Logarithmic-Depth Fermion Sampling: Anticoncentration and Average-Case Hardness
Natansh Mathur, Iordanis Kerenidis
Sampling problems give some of the clearest conditional separations between quantum and classical computation. In Fermion Sampling, passive linear optics acts on a non-Gaussian mag…
"Train classical, deploy quantum" requires rethinking generalization
Snehal Raj, Natansh Mathur, Alejandro Perdomo-Ortiz
Generative models have become central across science and industry, from image and text synthesis to the design of molecules and materials. Quantum generative models are considered…
Scalable On-Hardware Training of Quantum Neural Networks and Application to Clinical Data Imputation
Natansh Mathur, Panagiotis Kl. Barkoutsos, Masako Yamada +2
Training quantum neural networks (QNNs) on quantum hardware is currently bottlenecked by the cost of gradient estimation: standard parameter-shift methods require a number of circu…
Unsupervised Physics-Informed Operator Learning through Multi-Stage Curriculum Training
Paolo Marcandelli, Natansh Mathur, Stefano Markidis +2
Solving partial differential equations remains a central challenge in scientific machine learning. Neural operators offer a promising route by learning mappings between function sp…