Quantum Machine Learning

Benchmarks archive 2025-07-28

2 leaderboard tables shown for this task, 2 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 140 papers with code (699 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• PennyLane: Automatic differentiation of hybrid quantum-classical computations
  12 Nov 2018 27 repositories listed Syntology ran 0 of 25 samples · 25 unverified
  PennyLane's core feature is the ability to compute gradients of variational quantum circuits in a way that is compatible with classical techniques such as backpropagation.
• TensorFlow Quantum: A Software Framework for Quantum Machine Learning
  6 Mar 2020 4 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  We introduce TensorFlow Quantum (TFQ), an open source library for the rapid prototyping of hybrid quantum-classical models for classical or quantum data.
• Better than classical? The subtle art of benchmarking quantum machine learning models
  11 Mar 2024 3 repositories listed Syntology ran 2 of 2 samples · 0 unverified
  Benchmarking models via classical simulations is one of the main ways to judge ideas in quantum machine learning before noise-free hardware is available.
• A divide-and-conquer algorithm for quantum state preparation
  4 Aug 2020 3 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  Results show that we can efficiently load data in quantum devices using a divide-and-conquer strategy to exchange computational time for space.
• Qiskit Machine Learning: an open-source library for quantum machine learning tasks at scale on quantum hardware and classical simulators
  23 May 2025 2 repositories listed
  We present Qiskit Machine Learning (ML), a high-level Python library that combines elements of quantum computing with traditional machine learning.
• A Parameter-Efficient Quantum Anomaly Detection Method on a Superconducting Quantum Processor
  22 Dec 2024 2 repositories listed
  In this work, we propose a novel quantum machine learning method, called Parameter-Efficient Quantum Anomaly Detection (PEQAD), for practical image anomaly detection, which aims to achieve both parameter efficiency and…
• Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray Classification
  30 Apr 2024 2 repositories listed
  We evaluated the performance of our Jax-based framework in terms of efficiency and performance for hybrid quantum transfer learning for long-tailed classification across 8, 14, and 19 disease labels using large-scale…
• Application of Quantum Pre-Processing Filter for Binary Image Classification with Small Samples
  28 Aug 2023 2 repositories listed
  Similar to our previous multi-class classification results, the application of QPF improved the binary image classification accuracy using neural network against MNIST, EMNIST, and CIFAR-10 from 98.
• Application-Oriented Benchmarking of Quantum Generative Learning Using QUARK
  8 Aug 2023 2 repositories listed
  Benchmarking of quantum machine learning (QML) algorithms is challenging due to the complexity and variability of QML systems, e.
• Quantum Advantage Seeker with Kernels (QuASK): a software framework to speed up the research in quantum machine learning
  30 Jun 2022 2 repositories listed
  Our framework can also be used as a library and integrated into pre-existing software, maximizing code reuse.
• Equivariant quantum circuits for learning on weighted graphs
  12 May 2022 2 repositories listed
  When training a parametrized quantum circuit in this setting to solve a specific problem, the choice of ansatz is one of the most important factors that determines the trainability and performance of the algorithm.
• Quantum Deep Reinforcement Learning for Robot Navigation Tasks
  24 Feb 2022 2 repositories listed Syntology ran 0 of 9 samples · 9 unverified
  We utilize hybrid quantum deep reinforcement learning to learn navigation tasks for a simple, wheeled robot in simulated environments of increasing complexity.
• Practical distributed quantum information processing with LOCCNet
  28 Jan 2021 2 repositories listed
  Here we introduce LOCCNet, a machine learning framework facilitating protocol design and optimization for distributed quantum information processing tasks.
• Supervised quantum machine learning models are kernel methods
  26 Jan 2021 2 repositories listed
  With near-term quantum devices available and the race for fault-tolerant quantum computers in full swing, researchers became interested in the question of what happens if we replace a supervised machine learning model…
• The power of quantum neural networks
  30 Oct 2020 2 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  We show that quantum neural networks are able to achieve a significantly better effective dimension than comparable classical neural networks.
• Experimental Quantum Generative Adversarial Networks for Image Generation
  13 Oct 2020 2 repositories listed
  For the first time, we experimentally achieve the learning and generation of real-world hand-written digit images on a superconducting quantum processor.
• Reinforcement Learning with Quantum Variational Circuits
  15 Aug 2020 2 repositories listed
  This work explores the potential for quantum computing to facilitate reinforcement learning problems.
• q-means: A quantum algorithm for unsupervised machine learning
  10 Dec 2018 2 repositories listed Syntology ran 0 of 5 samples · 5 unverified
  For a natural notion of well-clusterable datasets, the running time becomes O( k² d (η^(2.
• Quantum Neuron: an elementary building block for machine learning on quantum computers
  30 Nov 2017 2 repositories listed
  In the construction of feedforward networks of quantum neurons, we provide numerical evidence that the network not only can learn a function when trained with superposition of inputs and the corresponding output, but…
• The interplay of robustness and generalization in quantum machine learning
  10 Jun 2025 1 repository listed
  While adversarial robustness and generalization have individually received substantial attention in the recent literature on quantum machine learning, their interplay is much less explored.
• Tensor Network for Anomaly Detection in the Latent Space of Proton Collision Events at the LHC
  30 May 2025 1 repository listed
  The pursuit of discovering new phenomena at the Large Hadron Collider (LHC) demands constant innovation in algorithms and technologies.
• QuXAI: Explainers for Hybrid Quantum Machine Learning Models
  15 May 2025 1 repository listed
  The gap is the focus of this work, which introduces QuXAI, an framework based upon Q-MEDLEY, an explainer for explaining feature importance in these hybrid systems.
• Distributed Quantum Neural Networks on Distributed Photonic Quantum Computing
  13 May 2025 1 repository listed
  We introduce a distributed quantum-classical framework that synergizes photonic quantum neural networks (QNNs) with matrix-product-state (MPS) mapping to achieve parameter-efficient training of classical neural networks.
• Quorum: Zero-Training Unsupervised Anomaly Detection using Quantum Autoencoders
  17 Apr 2025 1 repository listed
  Detecting mission-critical anomalous events and data is a crucial challenge across various industries, including finance, healthcare, and energy.
• Fine-Tuning Large Language Models on Quantum Optimization Problems for Circuit Generation
  15 Apr 2025 1 repository listed
  Large language models (LLM) have achieved remarkable outcomes in addressing complex problems, including math, coding, and analyzing large amounts of scientific reports.
• An Efficient Quantum Classifier Based on Hamiltonian Representations
  13 Apr 2025 1 repository listed
  To address these challenges, we propose an efficient approach called Hamiltonian classifier that circumvents the costs associated with data encoding by mapping inputs to a finite set of Pauli strings and computing…
• Automating quantum feature map design via large language models
  10 Apr 2025 1 repository listed
  Quantum feature maps are a key component of quantum machine learning, encoding classical data into quantum states to exploit the expressive power of high-dimensional Hilbert spaces.
• K-P Quantum Neural Networks
  2 Apr 2025 1 repository listed
  We present an extension of K-P time-optimal quantum control solutions using global Cartan KAK decompositions for geodesic-based solutions.
• Transforming Traditional Neural Networks into Neuromorphic Quantum-Cognitive Models: A Tutorial with Applications
  10 Mar 2025 1 repository listed
  Quantum technologies are increasingly pervasive, underpinning the operation of numerous electronic, optical and medical devices.
• CQ CNN: A Hybrid Classical Quantum Convolutional Neural Network for Alzheimer's Disease Detection Using Diffusion Generated and U Net Segmented 3D MRI
  4 Mar 2025 1 repository listed
  The detection of Alzheimer disease (AD) from clinical MRI data is an active area of research in medical imaging.

Syntology lines on 7 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.