Differential Privacy papers, 2023–2026

Key findings

• Differential Privacy fell from 117 papers in 2023 to 103 in 2026, so interest is cooling.
• NeurIPS publishes the most Differential Privacy work: 217 papers from 2023 to 2026, 45% of the four-venue total.
• The fastest-growing overlap is with Social aspects · accountability transparency and interpretability: papers tagged with both rose from 0 in 2023 to 22 in 2026.
• Among the 5 topics under Federated and Privacy, it ranks #3 by 2026 paper count; the fastest grower in the group, Secure Aggregation, is up 1.8x versus 0.9x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Unified Framework for Adversary-Aware Differential Privacy Bounds
• ICML 2026Optimal conversion from Rényi Differential Privacy to $f$-Differential Privacy
• ICLR 2026Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models
• CVPR 2026Fully Decentralized Certified Unlearning
• NeurIPS 2025Continual Release Moment Estimation with Differential Privacy
• ICML 2025Leveraging Per-Instance Privacy for Machine Unlearning
• ICLR 2025Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning
• CVPR 2025Focal Split: Untethered Snapshot Depth from Differential Defocus
• NeurIPS 2024$\texttt{pfl-research}$: simulation framework for accelerating research in Private Federated Learning
• ICML 2024Delving into Differentially Private Transformer
• ICLR 2024Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations
• CVPR 2024Affine Equivariant Networks Based on Differential Invariants
• NeurIPS 2023(Amplified) Banded Matrix Factorization: A unified approach to private training
• ICML 2023Bayesian Estimation of Differential Privacy
• ICLR 2023A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy
• CVPR 2023Learning To Generate Image Embeddings With User-Level Differential Privacy
• NeurIPS 2026Asymptotically Optimal Best Arm Identification with Fixed-Budget under Differential Privacy
• ICML 2026Optimization, Generalization and Differential Privacy Bounds for Gradient Descent on Kolmogorov–Arnold Networks
• ICLR 2026Beyond Membership: Limitations of Add/Remove Adjacency in Differential Privacy
• CVPR 2026LDP-Slicing Local Differential Privacy for Images via Randomized Bit-Plane Slicing

All Differential Privacy papers

21 papers, page 1 of 1

1. ICLR 2023A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy
2. ICLR 2023Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections
3. ICLR 2023CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning
4. ICLR 2023Characteristic Neural Ordinary Differential Equation
5. ICLR 2023Coupled Multiwavelet Operator Learning for Coupled Differential Equations
6. ICLR 2023Differentially Private $L_2$-Heavy Hitters in the Sliding Window Model
7. ICLR 2023Differentially Private Adaptive Optimization with Delayed Preconditioners
8. ICLR 2023Disparate Impact in Differential Privacy from Gradient Misalignment
9. ICLR 2023Distributed Differential Privacy in Multi-Armed Bandits
10. ICLR 2023Easy Differentially Private Linear Regression
11. ICLR 2023Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
12. ICLR 2023Improved Convergence of Differential Private SGD with Gradient Clipping
13. ICLR 2023Individual Privacy Accounting with Gaussian Differential Privacy
14. ICLR 2023Neural ePDOs: Spatially Adaptive Equivariant Partial Differential Operator Based Networks
15. ICLR 2023Private Federated Learning Without a Trusted Server: Optimal Algorithms for Convex Losses
16. ICLR 2023Regression with Label Differential Privacy
17. ICLR 2023Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning
18. ICLR 2023Statistical Theory of Differentially Private Marginal-based Data Synthesis Algorithms
19. ICLR 2023Stochastic Differentially Private and Fair Learning
20. ICLR 2023Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation
21. ICLR 2023Transformer Meets Boundary Value Inverse Problems

FAQ

How many Differential Privacy papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

479 in total: 117 in 2023, 113 in 2024, 146 in 2025, 103 in 2026.

How many Differential Privacy papers are at NeurIPS 2026?

NeurIPS 2026 has 23 Differential Privacy papers, versus 66 the year before.

How many Differential Privacy papers are at ICLR 2026?

ICLR 2026 has 31 Differential Privacy papers, versus 29 the year before.

How many Differential Privacy papers are at ICML 2026?

ICML 2026 has 42 Differential Privacy papers, versus 47 the year before.

How many Differential Privacy papers are at CVPR 2026?

CVPR 2026 has 7 Differential Privacy papers, versus 4 the year before.

Which conference publishes the most Differential Privacy papers?

NeurIPS, with 217 papers from 2023 to 2026.