Masoud Mohseni

According to our database, Masoud Mohseni authored at least 20 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Next-generation Probabilistic Computing Hardware with 3D MOSAICs, Illusion Scale-up, and Co-design.

Tathagata Srimani, Robert M. Radway, Masoud Mohseni, Kerem Yunus Çamsari, Subhasish Mitra

CoRR, 2024

Distributed Binary Optimization with In-Memory Computing: An Application for the SAT Problem.

Xiangyi Zhang, Ignacio Rozada, Fabian Böhm, Elisabetta Valiante, Moslem Noori, Thomas Van Vaerenbergh, Chan-Woo Yang, Giacomo Pedretti, Masoud Mohseni, Raymond G. Beausoleil

CoRR, 2024

Combinatorial Reasoning: Selecting Reasons in Generative AI Pipelines via Combinatorial Optimization.

Mert Esencan, Tarun Advaith Kumar, Ata Akbari Asanjan, P. Aaron Lott, Masoud Mohseni, Can Unlu, Davide Venturelli, Alan Ho

CoRR, 2024

2023

Training Deep Boltzmann Networks with Sparse Ising Machines.

Shaila Niazi, Navid Anjum Aadit, Masoud Mohseni, Shuvro Chowdhury, Yao Qin, Kerem Yunus Çamsari

CoRR, 2023

A full-stack view of probabilistic computing with p-bits: devices, architectures and algorithms.

Shuvro Chowdhury, Andrea Grimaldi, Navid Anjum Aadit, Shaila Niazi, Masoud Mohseni, Shun Kanai, Hideo Ohno, Shunsuke Fukami, Luke Theogarajan, Giovanni Finocchio, Supriyo Datta, Kerem Yunus Çamsari

CoRR, 2023

Accelerating Adaptive Parallel Tempering with FPGA-based p-bits.

Navid Anjum Aadit, Masoud Mohseni, Kerem Yunus Çamsari

Proceedings of the 2023 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits), 2023

2022

The physics of energy-based models.

Patrick Huembeli, Juan Miguel Arrazola, Nathan Killoran, Masoud Mohseni, Peter Wittek

Quantum Mach. Intell., 2022

2021

Layerwise learning for quantum neural networks.

Andrea Skolik, Jarrod R. McClean, Masoud Mohseni, Patrick van der Smagt, Martin Leib

Quantum Mach. Intell., 2021

Universal discriminative quantum neural networks.

Hongxiang Chen, Leonard Wossnig, Simone Severini, Hartmut Neven, Masoud Mohseni

Quantum Mach. Intell., 2021

Quantum advantage in learning from experiments.

Hsin-Yuan Huang, Michael Broughton, Jordan Cotler, Sitan Chen, Jerry Li, Masoud Mohseni, Hartmut Neven, Ryan Babbush, Richard Kueng, John Preskill, Jarrod R. McClean

CoRR, 2021

Nonequilibrium Monte Carlo for unfreezing variables in hard combinatorial optimization.

Masoud Mohseni, Daniel Eppens, Johan Strümpfer, Raffaele Marino, Vasil S. Denchev, Alan K. Ho, Sergei V. Isakov, Sergio Boixo, Federico Ricci-Tersenghi, Hartmut Neven

CoRR, 2021

2020

Power of data in quantum machine learning.

Hsin-Yuan Huang, Michael Broughton, Masoud Mohseni, Ryan Babbush, Sergio Boixo, Hartmut Neven, Jarrod R. McClean

CoRR, 2020

TensorFlow Quantum: A Software Framework for Quantum Machine Learning.

Michael Broughton, Guillaume Verdon, Trevor McCourt, Antonio J. Martinez, Jae Hyeon Yoo, Sergei V. Isakov, Philip Massey, Murphy Yuezhen Niu, Ramin Halavati, Evan Peters, Martin Leib, Andrea Skolik, Michael Streif, David Von Dollen, Jarrod R. McClean, Sergio Boixo, Dave Bacon, Alan K. Ho, Hartmut Neven, Masoud Mohseni

CoRR, 2020

A Probability Density Theory for Spin-Glass Systems.

Gavin S. Hartnett, Masoud Mohseni

CoRR, 2020

Self-Supervised Learning of Generative Spin-Glasses with Normalizing Flows.

Gavin S. Hartnett, Masoud Mohseni

CoRR, 2020

2019

Scaling advantage in quantum simulation of geometrically frustrated magnets.

Andrew D. King, Jack Raymond, Trevor Lanting, Sergei V. Isakov, Masoud Mohseni, Gabriel Poulin-Lamarre, Sara Ejtemaee, William Bernoudy, Isil Ozfidan, Anatoly Yu. Smirnov, Mauricio Reis, Fabio Altomare, Michael Babcock, Catia Baron, Andrew J. Berkley, Kelly Boothby, Paul I. Bunyk, Holly Christiani, Colin Enderud, Bram Evert, Richard Harris, Emile Hoskinson, Shuiyuan Huang, Kais Jooya, Ali Khodabandelou, Nicolas Ladizinsky, Ryan Li, Paul Aaron Lott, Allison J. R. MacDonald, Danica Marsden, Gaelen Marsden, Teresa Medina, Reza Molavi, Richard Neufeld, Mana Norouzpour, Travis Oh, Igor Pavlov, Ilya Perminov, Thomas Prescott, Chris Rich, Yuki Sato, Benjamin Sheldan, George Sterling, Loren J. Swenson, Nicholas Tsai, Mark H. Volkmann, Jed D. Whittaker, Warren Wilkinson, Jason Yao, Hartmut Neven, Jeremy P. Hilton, Eric Ladizinsky, Mark W. Johnson, Mohammad H. Amin

CoRR, 2019

Learning to learn with quantum neural networks via classical neural networks.

Guillaume Verdon, Michael Broughton, Jarrod R. McClean, Kevin J. Sung, Ryan Babbush, Zhang Jiang, Hartmut Neven, Masoud Mohseni

CoRR, 2019

Quantum-Assisted Genetic Algorithm.

James King, Masoud Mohseni, William Bernoudy, Alexandre Fréchette, Hossein Sadeghi, Sergei V. Isakov, Hartmut Neven, Mohammad H. Amin

CoRR, 2019

2018

Efficient Population Transfer via Non-Ergodic Extended States in Quantum Spin Glass.

Kostyantyn Kechedzhi, Vadim Smelyanskiy, Jarrod R. McClean, Vasil S. Denchev, Masoud Mohseni, Sergei Isakov, Sergio Boixo, Boris Altshuler, Hartmut Neven

Proceedings of the 13th Conference on the Theory of Quantum Computation, 2018

2013

Quantum support vector machine for big feature and big data classification.

Patrick Rebentrost, Masoud Mohseni, Seth Lloyd

CoRR, 2013