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

每年论文数

各会议论文数

按年份和会议统计

差分隐私论文数,按年份和会议
年份NeurIPSICLRICMLCVPR合计
20236721272117
20246125243113
20256629474146
20262331427103

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

全部差分隐私论文

共 479 篇,第 8 / 10 页

  1. NeurIPS 2024Provably Safe Neural Network Controllers via Differential Dynamic Logic
  2. NeurIPS 2024Public-data Assisted Private Stochastic Optimization: Power and Limitations
  3. NeurIPS 2024Reparameterization invariance in approximate Bayesian inference
  4. NeurIPS 2024Revisiting Differentially Private ReLU Regression
  5. NeurIPS 2024Sample-Efficient Private Learning of Mixtures of Gaussians
  6. NeurIPS 2024Scalable DP-SGD: Shuffling vs. Poisson Subsampling
  7. NeurIPS 2024Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators
  8. NeurIPS 2024The Limits of Differential Privacy in Online Learning
  9. NeurIPS 2024Truthful High Dimensional Sparse Linear Regression
  10. NeurIPS 2024Unified Mechanism-Specific Amplification by Subsampling and Group Privacy Amplification
  11. NeurIPS 2024Universal Exact Compression of Differentially Private Mechanisms
  12. NeurIPS 2024Wasserstein convergence of Cech persistence diagrams for samplings of submanifolds
  13. CVPR 2023Learning To Generate Image Embeddings With User-Level Differential Privacy
  14. CVPR 2023Privacy-Preserving Representations Are Not Enough: Recovering Scene Content From Camera Poses
  15. ICLR 2023A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy
  16. ICLR 2023Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections
  17. ICLR 2023CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning
  18. ICLR 2023Characteristic Neural Ordinary Differential Equation
  19. ICLR 2023Coupled Multiwavelet Operator Learning for Coupled Differential Equations
  20. ICLR 2023Differentially Private $L_2$-Heavy Hitters in the Sliding Window Model
  21. ICLR 2023Differentially Private Adaptive Optimization with Delayed Preconditioners
  22. ICLR 2023Disparate Impact in Differential Privacy from Gradient Misalignment
  23. ICLR 2023Distributed Differential Privacy in Multi-Armed Bandits
  24. ICLR 2023Easy Differentially Private Linear Regression
  25. ICLR 2023Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
  26. ICLR 2023Improved Convergence of Differential Private SGD with Gradient Clipping
  27. ICLR 2023Individual Privacy Accounting with Gaussian Differential Privacy
  28. ICLR 2023Neural ePDOs: Spatially Adaptive Equivariant Partial Differential Operator Based Networks
  29. ICLR 2023Private Federated Learning Without a Trusted Server: Optimal Algorithms for Convex Losses
  30. ICLR 2023Regression with Label Differential Privacy
  31. ICLR 2023Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning
  32. ICLR 2023Statistical Theory of Differentially Private Marginal-based Data Synthesis Algorithms
  33. ICLR 2023Stochastic Differentially Private and Fair Learning
  34. ICLR 2023Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation
  35. ICLR 2023Transformer Meets Boundary Value Inverse Problems
  36. ICML 2023A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining
  37. ICML 2023Algorithms for bounding contribution for histogram estimation under user-level privacy
  38. ICML 2023Bayesian Estimation of Differential Privacy
  39. ICML 2023Concurrent Shuffle Differential Privacy Under Continual Observation
  40. ICML 2023Controlled Differential Equations on Long Sequences via Non-standard Wavelets
  41. ICML 2023DIFF2: Differential Private Optimization via Gradient Differences for Nonconvex Distributed Learning
  42. ICML 2023Differential Privacy has Bounded Impact on Fairness in Classification
  43. ICML 2023Differential Privacy, Linguistic Fairness, and Training Data Influence: Impossibility and Possibility Theorems for Multilingual Language Models
  44. ICML 2023Differentially Private Sharpness-Aware Training
  45. ICML 2023Effectively Using Public Data in Privacy Preserving Machine Learning
  46. ICML 2023Federated Linear Contextual Bandits with User-level Differential Privacy
  47. ICML 2023Fully-Adaptive Composition in Differential Privacy
  48. ICML 2023Group Equivariant Fourier Neural Operators for Partial Differential Equations
  49. ICML 2023Image Restoration with Mean-Reverting Stochastic Differential Equations
  50. ICML 2023Label differential privacy and private training data release

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"}

两分钟接入 Paperlist MCP(Claude Code、Cursor、Codex、ChatGPT)

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。

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