Quantum Machine Learning papers, 2023–2026

Key findings

• Quantum Machine Learning fell from 72 papers in 2023 to 33 in 2026, so interest is cooling.
• NeurIPS publishes the most Quantum Machine Learning work: 77 papers from 2023 to 2026, 53% of the four-venue total.
• The fastest-growing overlap is with Applications · chemistry physics and earth sciences: papers tagged with both rose from 1 in 2023 to 5 in 2026.
• Among the 5 topics under Quantum and Exotic Computing, it ranks #2 by 2026 paper count; the fastest grower in the group, Neuromorphic Computing, is up 1.9x versus 0.5x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All Quantum Machine Learning papers

77 papers, page 1 of 2

1. NeurIPS 2026A Locality-Aware Surrogate for Natural-Gradient Descent in Quantum Optimization
2. NeurIPS 2026Beyond MNIST: Limitations of Amplitude Encoding on Quantum Classification
3. NeurIPS 2026BuresTomFlow: Bures-Geometric Flow Matching for Posterior Quantum Tomography
4. NeurIPS 2026Characterizing Trainability of Instantaneous Quantum Polynomial Circuit Born Machine
5. NeurIPS 2026Fast Accurate Quantum Monte Carlo without Metropolis Adjustment
6. NeurIPS 2026Optimal algorithmic complexity of inference in quantum kernel methods
7. NeurIPS 2026Quantum Best Arm Identification with Limited Round of Adaptivity: Lower Bounds and Algorithms
8. NeurIPS 2026Quantum Composite Hypothesis Testing with Small Error
9. NeurIPS 2026Quantum Speedup of Multi-armed Bandits at Scale by Tackling Memory Decoherence
10. NeurIPS 2026Score-based Variational Inference via Quantum Maximally Mixed States
11. NeurIPS 2026Sliced Wasserstein Meets Quantum Optics: Provable Wavefunctions Tomography with Scarce Noisy Measurements
12. NeurIPS 2026Stochastic Reconfiguration as Statistical Filtering for Overparameterized Neural Quantum States
13. NeurIPS 2026Stop Quantum Machine Learning; do AI-for-Quantum instead
14. NeurIPS 2026Structured Unitary Tensor Network Representations for Circuit-Efficient Quantum Data Encoding
15. NeurIPS 2026Symplectic Reck: In-Situ Learning of Gaussian Quantum Operations
16. NeurIPS 2026The Spectral Amplitude Principle for Dynamics of Quantum Neural Networks
17. NeurIPS 2026Training-Free Entangler Selection for Quantum Neural Networks via Hilbert–Schmidt Geometry
18. NeurIPS 2026Walking the Hypercube: Unbiased Quantum Partition Functions Without the Matrix
19. NeurIPS 2026Winning Lottery Tickets in Neural Networks via a Quantum-Inspired Classical Algorithm
20. NeurIPS 2025A Unified Framework for Provably Efficient Algorithms to Estimate Shapley Values
21. NeurIPS 2025Fast Zeroth-Order Convex Optimization with Quantum Gradient Methods
22. NeurIPS 2025Hadamard Test is Sufficient for Efficient Quantum Gradient Estimation with Lie Algebraic Symmetries
23. NeurIPS 2025Near-Optimal Quantum Algorithms for Computing (Coarse) Correlated Equilibria of General-Sum Games
24. NeurIPS 2025Purest Quantum State Identification
25. NeurIPS 2025Quantum Doubly Stochastic Transformers
26. NeurIPS 2025Quantum speedup of non-linear Monte Carlo problems
27. NeurIPS 2025Quantum Speedups for Minimax Optimization and Beyond
28. NeurIPS 2024Differentiable Quantum Computing for Large-scale Linear Control
29. NeurIPS 2024Non-asymptotic Approximation Error Bounds of Parameterized Quantum Circuits
30. NeurIPS 2024Predicting Ground State Properties: Constant Sample Complexity and Deep Learning Algorithms
31. NeurIPS 2024Quantum algorithm for large-scale market equilibrium computation
32. NeurIPS 2024Quantum Algorithms for Non-smooth Non-convex Optimization
33. NeurIPS 2024Quantum Deep Equilibrium Models
34. NeurIPS 2024Rethinking Parity Check Enhanced Symmetry-Preserving Ansatz
35. NeurIPS 2023$p$-value Adjustment for Monotonous, Unbiased, and Fast Clustering Comparison
36. NeurIPS 2023Advice Querying under Budget Constraint for Online Algorithms
37. NeurIPS 2023Auditing for Human Expertise
38. NeurIPS 2023Bicriteria Multidimensional Mechanism Design with Side Information
39. NeurIPS 2023Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning
40. NeurIPS 2023DISCO-10M: A Large-Scale Music Dataset
41. NeurIPS 2023Discrete-Smoothness in Online Algorithms with Predictions
42. NeurIPS 2023Estimating Koopman operators with sketching to provably learn large scale dynamical systems
43. NeurIPS 2023Fair, Polylog-Approximate Low-Cost Hierarchical Clustering
44. NeurIPS 2023Harnessing the power of choices in decision tree learning
45. NeurIPS 2023Have it your way: Individualized Privacy Assignment for DP-SGD
46. NeurIPS 2023Improved Frequency Estimation Algorithms with and without Predictions
47. NeurIPS 2023Incentives in Private Collaborative Machine Learning
48. NeurIPS 2023Intelligent Knee Sleeves: A Real-time Multimodal Dataset for 3D Lower Body Motion Estimation Using Smart Textile
49. NeurIPS 2023Logarithmic-Regret Quantum Learning Algorithms for Zero-Sum Games
50. NeurIPS 2023M$^2$Hub: Unlocking the Potential of Machine Learning for Materials Discovery

FAQ

How many Quantum Machine Learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

144 in total: 72 in 2023, 20 in 2024, 19 in 2025, 33 in 2026.

How many Quantum Machine Learning papers are at NeurIPS 2026?

NeurIPS 2026 has 19 Quantum Machine Learning papers, versus 8 the year before.

How many Quantum Machine Learning papers are at ICLR 2026?

ICLR 2026 has 4 Quantum Machine Learning papers, versus 3 the year before.

How many Quantum Machine Learning papers are at ICML 2026?

ICML 2026 has 10 Quantum Machine Learning papers, versus 8 the year before.

How many Quantum Machine Learning papers are at CVPR 2024?

CVPR 2024 has 2 Quantum Machine Learning papers, versus 1 the year before.

Which conference publishes the most Quantum Machine Learning papers?

NeurIPS, with 77 papers from 2023 to 2026.