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Masoud Mohseni
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2020 – today
- 2024
- [i17]Mert Esencan, Tarun Advaith Kumar, Ata Akbari Asanjan, P. Aaron Lott, Masoud Mohseni, Can Unlu, Davide Venturelli, Alan Ho:
Combinatorial Reasoning: Selecting Reasons in Generative AI Pipelines via Combinatorial Optimization. CoRR abs/2407.00071 (2024) - [i16]Xiangyi Zhang, Ignacio Rozada, Fabian Böhm, Elisabetta Valiante, Moslem Noori, Thomas Van Vaerenbergh, Chan-Woo Yang, Giacomo Pedretti, Masoud Mohseni, Raymond G. Beausoleil:
Distributed Binary Optimization with In-Memory Computing: An Application for the SAT Problem. CoRR abs/2409.09152 (2024) - [i15]Tathagata Srimani, Robert M. Radway, Masoud Mohseni, Kerem Yunus Çamsari, Subhasish Mitra:
Next-generation Probabilistic Computing Hardware with 3D MOSAICs, Illusion Scale-up, and Co-design. CoRR abs/2409.11422 (2024) - 2023
- [c2]Navid Anjum Aadit, Masoud Mohseni, Kerem Yunus Çamsari:
Accelerating Adaptive Parallel Tempering with FPGA-based p-bits. VLSI Technology and Circuits 2023: 1-2 - [i14]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
A full-stack view of probabilistic computing with p-bits: devices, architectures and algorithms. CoRR abs/2302.06457 (2023) - [i13]Shaila Niazi, Navid Anjum Aadit, Masoud Mohseni, Shuvro Chowdhury, Yao Qin, Kerem Yunus Çamsari:
Training Deep Boltzmann Networks with Sparse Ising Machines. CoRR abs/2303.10728 (2023) - 2022
- [j3]Patrick Huembeli
The physics of energy-based models. Quantum Mach. Intell. 4(1) (2022) - 2021
- [j2]Hongxiang Chen
Universal discriminative quantum neural networks. Quantum Mach. Intell. 3(1): 1-11 (2021) - [j1]Andrea Skolik
Layerwise learning for quantum neural networks. Quantum Mach. Intell. 3(1): 1-11 (2021) - [i12]Masoud Mohseni, Daniel Eppens, Johan Strümpfer, Raffaele Marino, Vasil S. Denchev, Alan K. Ho, Sergei V. Isakov, Sergio Boixo, Federico Ricci-Tersenghi, Hartmut Neven:
Nonequilibrium Monte Carlo for unfreezing variables in hard combinatorial optimization. CoRR abs/2111.13628 (2021) - [i11]Hsin-Yuan Huang, Michael Broughton, Jordan Cotler, Sitan Chen, Jerry Li, Masoud Mohseni, Hartmut Neven, Ryan Babbush, Richard Kueng, John Preskill, Jarrod R. McClean:
Quantum advantage in learning from experiments. CoRR abs/2112.00778 (2021) - 2020
- [i10]Gavin S. Hartnett, Masoud Mohseni:
Self-Supervised Learning of Generative Spin-Glasses with Normalizing Flows. CoRR abs/2001.00585 (2020) - [i9]Gavin S. Hartnett, Masoud Mohseni:
A Probability Density Theory for Spin-Glass Systems. CoRR abs/2001.00927 (2020) - [i8]Michael Broughton, Guillaume Verdon, Trevor McCourt, Antonio J. Martinez, Jae Hyeon Yoo, Sergei V. Isakov, Philip Massey, Murphy Yuezhen Niu, Ramin Halavati, Evan Peters
TensorFlow Quantum: A Software Framework for Quantum Machine Learning. CoRR abs/2003.02989 (2020) - [i7]Andrea Skolik, Jarrod R. McClean, Masoud Mohseni, Patrick van der Smagt, Martin Leib:
Layerwise learning for quantum neural networks. CoRR abs/2006.14904 (2020) - [i6]Hsin-Yuan Huang, Michael Broughton, Masoud Mohseni, Ryan Babbush, Sergio Boixo, Hartmut Neven, Jarrod R. McClean:
Power of data in quantum machine learning. CoRR abs/2011.01938 (2020)
2010 – 2019
- 2019
- [i5]James King, Masoud Mohseni, William Bernoudy, Alexandre Fréchette, Hossein Sadeghi, Sergei V. Isakov, Hartmut Neven, Mohammad H. Amin:
Quantum-Assisted Genetic Algorithm. CoRR abs/1907.00707 (2019) - [i4]Guillaume Verdon, Michael Broughton, Jarrod R. McClean, Kevin J. Sung, Ryan Babbush, Zhang Jiang, Hartmut Neven, Masoud Mohseni:
Learning to learn with quantum neural networks via classical neural networks. CoRR abs/1907.05415 (2019) - [i3]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
Scaling advantage in quantum simulation of geometrically frustrated magnets. CoRR abs/1911.03446 (2019) - 2018
- [c1]Kostyantyn Kechedzhi, Vadim Smelyanskiy, Jarrod R. McClean, Vasil S. Denchev, Masoud Mohseni, Sergei Isakov, Sergio Boixo, Boris Altshuler, Hartmut Neven:
Efficient Population Transfer via Non-Ergodic Extended States in Quantum Spin Glass. TQC 2018: 9:1-9:16 - [i2]Hongxiang Chen
Universal discriminative quantum neural networks. CoRR abs/1805.08654 (2018) - 2013
- [i1]Patrick Rebentrost, Masoud Mohseni, Seth Lloyd:
Quantum support vector machine for big feature and big data classification. CoRR abs/1307.0471 (2013)
Coauthor Index
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