Awesome Disordered Systems & Neural Networks

Adiabatic Bottlenecks In Quantum Annealing And Nonequilibrium Dynamics Of Paramagnons (2024)

Tim Bode, Frank K. Wilhelm

4.52

An Hybrid Quantum-Classical Diffusion Model for Image Generation (2026)

Qipeng Qian et al.

4.33

Optimal recovery for quantum error correction (2026)

Sun Woo P. Kim

1.72

Distributed Quantum Computing via Adaptive Circuit Knitting (2026)

K. Grace Johnson et al.

1.72

Teleportation transition of surface codes on a superconducting quantum processor (2026)

Yiren Zou et al.

1.67

Noisy Monitored Quantum Circuits (2025)

Shuo Liu et al.

1.56

Topology-Enhanced Superconducting Qubit Networks for In-Sensor Quantum Information Processing (2025)

J. Settino et al.

1.28

Deep-learned error mitigation via partially knitted circuits for the variational quantum eigensolver (2025)

Simone Cantori et al.

1.22

Correcting a noisy quantum computer using a quantum computer (2025)

Pan Zhang

1.22

Microscopic Properties Of Quantum Annealing -- Application To Fully Frustrated Ising Systems (2011)

Shu Tanaka

0.00

Effect Of Noise On Quantum Circuit Realization Of Non-hermitian Time Crystals (2024)

Weihua Xie, Michael Kolodrubetz, Vadim Oganesyan

0.00

Machine-learning-assisted correction of correlated qubit errors in a topological code (2017)

P. Baireuther et al.

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A quantum algorithm to train neural networks using low-depth circuits (2017)

Guillaume Verdon et al.

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Information Scrambling in Quantum Neural Networks (2019)

Huitao Shen et al.

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Certified variational quantum algorithms for eigenstate preparation (2020)

Andrey Kardashin and Alexey Uvarov and Dmitry Yudin and Jacob Biamonte

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Qubit-efficient encoding schemes for binary optimisation problems (2020)

Benjamin Tan et al.

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Generating highly entangled states via discrete-time quantum walks with Parrondo sequences (2020)

Dinesh Kumar Panda et al.

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Quantum coding with low-depth random circuits (2020)

Michael J. Gullans et al.

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Automatic virtual voltage extraction of a 2x2 array of quantum dots with machine learning (2020)

Giovanni A. Oakes et al.

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Training Saturation in Layerwise Quantum Approximate Optimisation (2021)

E. Campos et al.

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Generalized quantum circuit differentiation rules (2021)

Oleksandr Kyriienko et al.

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Data compression for quantum machine learning (2022)

Rohit Dilip et al.

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Experimental quantum pattern recognition in IBMQ and diamond NVs (2022)

Sreetama Das et al.

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Quantum annealing sampling with a bias field (2022)

Tobias Gra{\ss}

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Improving the performance of quantum approximate optimization for preparing non-trivial quantum states without translational symmetry (2022)

Zheng-Hang Sun et al.

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Recursive greedy initialization of the quantum approximate optimization algorithm with guaranteed improvement (2022)

Stefan H. Sack et al.

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Quantum reservoir neural network implementation on coherently coupled quantum oscillators (2022)

Julien Dudas et al.

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Navigating the noise-depth tradeoff in adiabatic quantum circuits (2022)

Daniel Azses et al.

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Kernel Learning by quantum annealer (2023)

Yasushi Hasegawa et al.

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Stabilization of symmetry-protected long-range entanglement in stochastic quantum circuits (2023)

Iosifina Angelidi et al.

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What can we learn from quantum convolutional neural networks? (2023)

Chukwudubem Umeano et al.

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Realizing the Nishimori transition across the error threshold for constant-depth quantum circuits (2023)

Edward H. Chen et al.

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Mitigating crosstalk and residual coupling errors in superconducting quantum processors using many-body localization (2023)

Peng Qian et al.

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Advantage of Quantum Neural Networks as Quantum Information Decoders (2024)

Weishun Zhong et al.

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Madelyn Cain et al.

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Fermionic Machine Learning (2024)

J\'er\'emie Gince et al.

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Large-scale quantum reservoir learning with an analog quantum computer (2024)

Milan Kornja\v{c}a et al.

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Coherent Information Phase Transition in a Noisy Quantum Circuit (2024)

Dongheng Qian and Jing Wang

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Investigating layer-selective transfer learning of QAOA parameters for Max-Cut problem (2024)

Francesco Aldo Venturelli et al.

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Flow to Nishimori universality in weakly monitored quantum circuits with qubit loss (2025)

Malte P\"utz et al.

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Awesome Disordered Systems & Neural Networks

Datasets & benchmarks

Key papers

Disordered Systems & Neural Networks

Awesome Disordered Systems & Neural Networks

Datasets & benchmarks

Key papers