10 citations · 10 across the 6 of their papers we have counts for
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Prospects for quantum advantage in machine learning from the representability of functions
Sergi Masot-Llima, Elies Gil-Fuster, Carlos Bravo-Prieto +2
Demonstrating quantum advantage in machine learning tasks requires navigating a complex landscape of proposed models and algorithms. To bring clarity to this search, we introduce a…
Complexity of geometrically local stoquastic Hamiltonians
Asad Raza, Jens Eisert, Alex B. Grilo
The QMA-completeness of the local Hamiltonian problem is a landmark result of the field of Hamiltonian complexity that studies the computational complexity of problems in quantum m…
Towards efficient quantum algorithms for diffusion probabilistic models
Yunfei Wang, Ruoxi Jiang, Yingda Fan +4
A diffusion probabilistic model (DPM) is a generative model renowned for its ability to produce high-quality outputs in tasks such as image and audio generation. However, training…
Optimal trace-distance bounds for free-fermionic states: Testing and improved tomography
Lennart Bittel, Antonio Anna Mele, Jens Eisert +1
Free-fermionic states, also known as fermionic Gaussian states, represent an important class of quantum states ubiquitous in physics. They are uniquely and efficiently described by…
Artificial intelligence for representing and characterizing quantum systems
Yuxuan Du, Yan Zhu, Yuan-Hang Zhang +8
Efficient characterization of large-scale quantum systems, especially those produced by quantum analog simulators and megaquop quantum computers, poses a central challenge in quant…
Quantum reinforcement learning of classical rare dynamics: Enhancement by intrinsic Fourier features
Alissa Wilms, Laura Ohff, Andrea Skolik +3
Rare events are essential for understanding the behavior of non-equilibrium and industrial systems. It is of ongoing interest to develop methods for effectively searching for rare…