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

144 papers, page 3 of 3

101. ICML 2023Underspecification Presents Challenges for Credibility in Modern Machine Learning
102. NeurIPS 2023$p$-value Adjustment for Monotonous, Unbiased, and Fast Clustering Comparison
103. NeurIPS 2023Advice Querying under Budget Constraint for Online Algorithms
104. NeurIPS 2023Auditing for Human Expertise
105. NeurIPS 2023Bicriteria Multidimensional Mechanism Design with Side Information
106. NeurIPS 2023Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning
107. NeurIPS 2023DISCO-10M: A Large-Scale Music Dataset
108. NeurIPS 2023Discrete-Smoothness in Online Algorithms with Predictions
109. NeurIPS 2023Estimating Koopman operators with sketching to provably learn large scale dynamical systems
110. NeurIPS 2023Fair, Polylog-Approximate Low-Cost Hierarchical Clustering
111. NeurIPS 2023Harnessing the power of choices in decision tree learning
112. NeurIPS 2023Have it your way: Individualized Privacy Assignment for DP-SGD
113. NeurIPS 2023Improved Frequency Estimation Algorithms with and without Predictions
114. NeurIPS 2023Incentives in Private Collaborative Machine Learning
115. NeurIPS 2023Intelligent Knee Sleeves: A Real-time Multimodal Dataset for 3D Lower Body Motion Estimation Using Smart Textile
116. NeurIPS 2023Logarithmic-Regret Quantum Learning Algorithms for Zero-Sum Games
117. NeurIPS 2023M$^2$Hub: Unlocking the Potential of Machine Learning for Materials Discovery
118. NeurIPS 2023Machine learning detects terminal singularities
119. NeurIPS 2023MLFMF: Data Sets for Machine Learning for Mathematical Formalization
120. NeurIPS 2023MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under nonparametrized geometrical variability
121. NeurIPS 2023Model Sparsity Can Simplify Machine Unlearning
122. NeurIPS 2023Nonparametric Teaching for Multiple Learners
123. NeurIPS 2023On quantum backpropagation, information reuse, and cheating measurement collapse
124. NeurIPS 2023On the Importance of Feature Separability in Predicting Out-Of-Distribution Error
125. NeurIPS 2023Optimal privacy guarantees for a relaxed threat model: Addressing sub-optimal adversaries in differentially private machine learning
126. NeurIPS 2023Path following algorithms for $\ell_2$-regularized $M$-estimation with approximation guarantee
127. NeurIPS 2023Payoff-based Learning with Matrix Multiplicative Weights in Quantum Games
128. NeurIPS 2023QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules
129. NeurIPS 2023QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning
130. NeurIPS 2023Quantum Bayesian Optimization
131. NeurIPS 2023Quantum speedups for stochastic optimization
132. NeurIPS 2023Resilient Constrained Learning
133. NeurIPS 2023SALSA VERDE: a machine learning attack on LWE with sparse small secrets
134. NeurIPS 2023Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations
135. NeurIPS 2023Sorting with Predictions
136. NeurIPS 2023Statistical Analysis of Quantum State Learning Process in Quantum Neural Networks
137. NeurIPS 2023Tanimoto Random Features for Scalable Molecular Machine Learning
138. NeurIPS 2023Temporal Robustness against Data poisoning
139. NeurIPS 2023Tester-Learners for Halfspaces: Universal Algorithms
140. NeurIPS 2023The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance
141. NeurIPS 2023UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition
142. NeurIPS 2023Variational Monte Carlo on a Budget — Fine-tuning pre-trained Neural Wavefunctions
143. NeurIPS 2023Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation
144. NeurIPS 2023Weighted ROC Curve in Cost Space: Extending AUC to Cost-Sensitive Learning

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.