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 49 篇，第 1 / 1 页

1. ICML 2026A Sketch-and-Project Analysis of Subsampled Natural Gradient Algorithms
2. ICML 2026Accelerating Regression Tasks with Quantum Algorithms
3. ICML 2026An Exponential Separation Between Quantum and Quantum-Inspired Classical Algorithms for Linear Systems
4. ICML 2026Optimal Quantum Speedups for Repeatedly Nested Expectation Estimation
5. ICML 2026Procedural Generation Of Algorithm Discovery Tasks in Machine Learning
6. ICML 2026Quantum Algorithms for Triangle Cut Sparsification
7. ICML 2026Quantum latent distributions in deep generative models
8. ICML 2026QuantumBoost: A lazy, yet fast, quantum algorithm for learning with weak hypotheses
9. ICML 2026SAQNN: Spectral Adaptive Quantum Neural Network as a Universal Approximator
10. ICML 2026Transformer Circuits Can Realize Clustering Algorithms
11. ICML 2025A Sub-Problem Quantum Alternating Operator Ansatz for Correlation Clustering
12. ICML 2025Benchmarking Quantum Reinforcement Learning
13. ICML 2025Compact Matrix Quantum Group Equivariant Neural Networks
14. ICML 2025Limitations of measure-first protocols in quantum machine learning
15. ICML 2025Predictive Performance of Deep Quantum Data Re-uploading Models
16. ICML 2025Quantum Algorithms for Finite-horizon Markov Decision Processes
17. ICML 2025Quantum Optimization via Gradient-Based Hamiltonian Descent
18. ICML 2025Quantum Speedup for Hypergraph Sparsification
19. ICML 2024Gibbs Sampling of Continuous Potentials on a Quantum Computer
20. ICML 2024Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret
21. ICML 2024QBMK: Quantum-based Matching Kernels for Un-attributed Graphs
22. ICML 2024Quantum Algorithms and Lower Bounds for Finite-Sum Optimization
23. ICML 2024Quantum Implicit Neural Representations
24. ICML 2024Stochastic Quantum Sampling for Non-Logconcave Distributions and Estimating Partition Functions
25. ICML 2024The Role of Learning Algorithms in Collective Action
26. ICML 2023A Hybrid Quantum-Classical Approach based on the Hadamard Transform for the Convolutional Layer
27. ICML 2023Action Matching: Learning Stochastic Dynamics from Samples
28. ICML 2023Adaptive Identification of Populations with Treatment Benefit in Clinical Trials: Machine Learning Challenges and Solutions
29. ICML 2023Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano
30. ICML 2023Attribute-Efficient PAC Learning of Low-Degree Polynomial Threshold Functions with Nasty Noise
31. ICML 2023Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning
32. ICML 2023Efficient Quantum Algorithms for Quantum Optimal Control
33. ICML 2023From Adaptive Query Release to Machine Unlearning
34. ICML 2023Inflow, Outflow, and Reciprocity in Machine Learning
35. ICML 2023Learning Distributions over Quantum Measurement Outcomes
36. ICML 2023Learning-augmented private algorithms for multiple quantile release
37. ICML 2023Machine Learning Force Fields with Data Cost Aware Training
38. ICML 2023Near-Optimal Quantum Coreset Construction Algorithms for Clustering
39. ICML 2023Principled Acceleration of Iterative Numerical Methods Using Machine Learning
40. ICML 2023QAS-Bench: Rethinking Quantum Architecture Search and A Benchmark
41. ICML 2023Quantum Lower Bounds for Finding Stationary Points of Nonconvex Functions
42. ICML 2023Quantum Policy Gradient Algorithm with Optimized Action Decoding
43. ICML 2023Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation
44. ICML 2023QuantumDARTS: Differentiable Quantum Architecture Search for Variational Quantum Algorithms
45. ICML 2023Selective Machine Learning of the Average Treatment Effect with an Invalid Instrumental Variable
46. ICML 2023Solving Linear Programs with Fast Online Learning Algorithms
47. ICML 2023Statistical Indistinguishability of Learning Algorithms
48. ICML 2023Towards Quantum Machine Learning for Constrained Combinatorial Optimization: a Quantum QAP Solver
49. ICML 2023Underspecification Presents Challenges for Credibility in Modern Machine 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。