4 papers
Discrete Feynman-Kac Correctors
Mohsin Hasan, Viktor Ohanesian, Artem Gazizov +5
Discrete diffusion models have recently emerged as a promising alternative to the autoregressive approach for generating discrete sequences. Sample generation via gradual denoising…
Assessing Quantum Advantage for Gaussian Process Regression
Dominic Lowe, M. S. Kim, Roberto Bondesan
Gaussian Process Regression is a well-known machine learning technique for which several quantum algorithms have been proposed. We show here that in a wide range of scenarios these…
Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts
Marta Skreta, Tara Akhound-Sadegh, Viktor Ohanesian +6
While score-based generative models are the model of choice across diverse domains, there are limited tools available for controlling inference-time behavior in a principled manner…
Efficient Learning of Long-Range and Equivariant Quantum Systems
Å tÄpán Å mÃd, Roberto Bondesan
In this work, we consider a fundamental task in quantum many-body physics - finding and learning ground states of quantum Hamiltonians and their properties. Recent works have studi…