量子机器学习论文趋势 2023–2026

主要结论

• 量子机器学习论文从 2023 年的 72 篇降到 2026 年的 33 篇，热度在回落。
• NeurIPS 是发量子机器学习论文最多的会议，2023–2026 年共 77 篇，占四个会议总量的 53%。
• 交叉方向里涨得最快的是应用 · chemistry physics and earth sciences：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 5 篇。
• 在「量子与其他」的 5 个主题里，它的 2026 年论文数排第 2；同组增长最快的神经形态计算是 1.9 倍，量子机器学习是 0.5 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• NeurIPS 2026Beyond MNIST: Limitations of Amplitude Encoding on Quantum Classification
• ICML 2026Accelerating Regression Tasks with Quantum Algorithms
• ICLR 2026Accelerating Inference for Multilayer Neural Networks with Quantum Computers
• NeurIPS 2025A Unified Framework for Provably Efficient Algorithms to Estimate Shapley Values
• ICML 2025Compact Matrix Quantum Group Equivariant Neural Networks
• ICLR 2025Exploring channel distinguishability in local neighborhoods of the model space in quantum neural networks
• NeurIPS 2024Differentiable Quantum Computing for Large-scale Linear Control
• ICML 2024Quantum Implicit Neural Representations
• ICLR 2024Topological data analysis on noisy quantum computers
• CVPR 2024HDQMF: Holographic Feature Decomposition Using Quantum Algorithms
• NeurIPS 2023Harnessing the power of choices in decision tree learning
• ICML 2023Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano
• ICLR 2023Classically Approximating Variational Quantum Machine Learning with Random Fourier Features
• CVPR 2023CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes
• NeurIPS 2026Characterizing Trainability of Instantaneous Quantum Polynomial Circuit Born Machine
• ICML 2026An Exponential Separation Between Quantum and Quantum-Inspired Classical Algorithms for Linear Systems
• ICLR 2026SAQ: Stabilizer-Aware Quantum Error Correction Decoder
• NeurIPS 2025Hadamard Test is Sufficient for Efficient Quantum Gradient Estimation with Lie Algebraic Symmetries
• ICML 2025A Sub-Problem Quantum Alternating Operator Ansatz for Correlation Clustering
• ICLR 2025Learning the Complexity of Weakly Noisy Quantum States

全部量子机器学习论文

共 77 篇，第 2 / 2 页

51. NeurIPS 2023Machine learning detects terminal singularities
52. NeurIPS 2023MLFMF: Data Sets for Machine Learning for Mathematical Formalization
53. NeurIPS 2023MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under nonparametrized geometrical variability
54. NeurIPS 2023Model Sparsity Can Simplify Machine Unlearning
55. NeurIPS 2023Nonparametric Teaching for Multiple Learners
56. NeurIPS 2023On quantum backpropagation, information reuse, and cheating measurement collapse
57. NeurIPS 2023On the Importance of Feature Separability in Predicting Out-Of-Distribution Error
58. NeurIPS 2023Optimal privacy guarantees for a relaxed threat model: Addressing sub-optimal adversaries in differentially private machine learning
59. NeurIPS 2023Path following algorithms for $\ell_2$-regularized $M$-estimation with approximation guarantee
60. NeurIPS 2023Payoff-based Learning with Matrix Multiplicative Weights in Quantum Games
61. NeurIPS 2023QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules
62. NeurIPS 2023QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning
63. NeurIPS 2023Quantum Bayesian Optimization
64. NeurIPS 2023Quantum speedups for stochastic optimization
65. NeurIPS 2023Resilient Constrained Learning
66. NeurIPS 2023SALSA VERDE: a machine learning attack on LWE with sparse small secrets
67. NeurIPS 2023Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations
68. NeurIPS 2023Sorting with Predictions
69. NeurIPS 2023Statistical Analysis of Quantum State Learning Process in Quantum Neural Networks
70. NeurIPS 2023Tanimoto Random Features for Scalable Molecular Machine Learning
71. NeurIPS 2023Temporal Robustness against Data poisoning
72. NeurIPS 2023Tester-Learners for Halfspaces: Universal Algorithms
73. NeurIPS 2023The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance
74. NeurIPS 2023UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition
75. NeurIPS 2023Variational Monte Carlo on a Budget — Fine-tuning pre-trained Neural Wavefunctions
76. NeurIPS 2023Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation
77. NeurIPS 2023Weighted ROC Curve in Cost Space: Extending AUC to Cost-Sensitive Learning

常见问题

2023–2026 年四大会议一共有多少篇量子机器学习论文？

共 144 篇，按年份分别是 2023 年 72 篇、2024 年 20 篇、2025 年 19 篇、2026 年 33 篇。

NeurIPS 2026 有多少篇量子机器学习论文？

NeurIPS 2026 有 19 篇量子机器学习论文，上一届是 8 篇。

ICLR 2026 有多少篇量子机器学习论文？

ICLR 2026 有 4 篇量子机器学习论文，上一届是 3 篇。

ICML 2026 有多少篇量子机器学习论文？

ICML 2026 有 10 篇量子机器学习论文，上一届是 8 篇。

CVPR 2024 有多少篇量子机器学习论文？

CVPR 2024 有 2 篇量子机器学习论文，上一届是 1 篇。

哪个会议的量子机器学习论文最多？

NeurIPS，2023–2026 年共 77 篇。