差分隐私论文趋势 2023–2026
DP 训练
统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 479 篇被归入该主题的论文。
主要结论
- 差分隐私论文从 2023 年的 117 篇降到 2026 年的 103 篇,热度在回落。
- NeurIPS 是发差分隐私论文最多的会议,2023–2026 年共 217 篇,占四个会议总量的 45%。
- 交叉方向里涨得最快的是社会层面 · accountability transparency and interpretability:同时属于两个主题的论文从 2023 年的 0 篇增至 2026 年的 22 篇。
- 在「联邦与隐私」的 5 个主题里,它的 2026 年论文数排第 3;同组增长最快的安全聚合是 1.8 倍,差分隐私是 0.9 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 67 | 21 | 27 | 2 | 117 |
| 2024 | 61 | 25 | 24 | 3 | 113 |
| 2025 | 66 | 29 | 47 | 4 | 146 |
| 2026 | 23 | 31 | 42 | 7 | 103 |
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 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
全部差分隐私论文
共 21 篇,第 1 / 1 页
- ICLR 2023A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy
- ICLR 2023Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections
- ICLR 2023CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning
- ICLR 2023Characteristic Neural Ordinary Differential Equation
- ICLR 2023Coupled Multiwavelet Operator Learning for Coupled Differential Equations
- ICLR 2023Differentially Private $L_2$-Heavy Hitters in the Sliding Window Model
- ICLR 2023Differentially Private Adaptive Optimization with Delayed Preconditioners
- ICLR 2023Disparate Impact in Differential Privacy from Gradient Misalignment
- ICLR 2023Distributed Differential Privacy in Multi-Armed Bandits
- ICLR 2023Easy Differentially Private Linear Regression
- ICLR 2023Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
- ICLR 2023Improved Convergence of Differential Private SGD with Gradient Clipping
- ICLR 2023Individual Privacy Accounting with Gaussian Differential Privacy
- ICLR 2023Neural ePDOs: Spatially Adaptive Equivariant Partial Differential Operator Based Networks
- ICLR 2023Private Federated Learning Without a Trusted Server: Optimal Algorithms for Convex Losses
- ICLR 2023Regression with Label Differential Privacy
- ICLR 2023Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning
- ICLR 2023Statistical Theory of Differentially Private Marginal-based Data Synthesis Algorithms
- ICLR 2023Stochastic Differentially Private and Fair Learning
- ICLR 2023Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation
- ICLR 2023Transformer Meets Boundary Value Inverse Problems
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后,写综述、挑方向或准备投稿时,不用离开对话框就能拿到这页的数字:每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文,AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查差分隐私在 NeurIPS 2023–2026 的论文趋势,哪一年涨得最快?
AI 会调用的工具:get_topic_stats {"topic": "differential-privacy"}
常见问题
- 2023–2026 年四大会议一共有多少篇差分隐私论文?
- 共 479 篇,按年份分别是 2023 年 117 篇、2024 年 113 篇、2025 年 146 篇、2026 年 103 篇。
- NeurIPS 2026 有多少篇差分隐私论文?
- NeurIPS 2026 有 23 篇差分隐私论文,上一届是 66 篇。
- ICLR 2026 有多少篇差分隐私论文?
- ICLR 2026 有 31 篇差分隐私论文,上一届是 29 篇。
- ICML 2026 有多少篇差分隐私论文?
- ICML 2026 有 42 篇差分隐私论文,上一届是 47 篇。
- CVPR 2026 有多少篇差分隐私论文?
- CVPR 2026 有 7 篇差分隐私论文,上一届是 4 篇。
- 哪个会议的差分隐私论文最多?
- NeurIPS,2023–2026 年共 217 篇。