表格深度学习论文趋势 2023–2026
表格数据建模
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 214 篇被归入该主题的论文。
主要结论
- 表格深度学习论文从 2023 年的 150 篇降到 2026 年的 33 篇，热度在回落。
- NeurIPS 是发表格深度学习论文最多的会议，2023–2026 年共 133 篇，占四个会议总量的 62%。
- 交叉方向里涨得最快的是驾驶仿真：同时属于两个主题的论文从 2023 年的 3 篇增至 2026 年的 6 篇。
- 在「图与结构化数据」的 5 个主题里，它的 2026 年论文数排第 5；同组增长最快的时间序列是 3.2 倍，表格深度学习是 0.2 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 115 | 6 | 29 | 0 | 150 |
| 2024 | 4 | 4 | 9 | 0 | 17 |
| 2025 | 5 | 6 | 3 | 0 | 14 |
| 2026 | 9 | 1 | 22 | 1 | 33 |
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 2026Coherent Routing in Decision Trees: Phase-Interference Learning for Interpretable Tabular Prediction
- ICML 2026Density-Guided Robust Counterfactual Explanations on Tabular Data under Model Multiplicity
- ICLR 2026Harpoon: Generalised Manifold Guidance for Conditional Tabular Diffusion
- CVPR 2026MultiModalPFN Extending Prior-Data Fitted Networks for Multimodal Tabular Learning
- NeurIPS 2025ConTextTab: A Semantics-Aware Tabular In-Context Learner
- ICML 2025Latent Score-Based Reweighting for Robust Classification on Imbalanced Tabular Data
- ICLR 2025Revisiting Nearest Neighbor for Tabular Data: A Deep Tabular Baseline Two Decades Later
- NeurIPS 2024WikiDBs: A Large-Scale Corpus Of Relational Databases From Wikidata
- ICML 2024BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model
- ICLR 2024GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data
- NeurIPS 2023Accurate Interpolation for Scattered Data through Hierarchical Residual Refinement
- ICML 2023Compressing Tabular Data via Latent Variable Estimation
- ICLR 2023TabCaps: A Capsule Neural Network for Tabular Data Classification with BoW Routing
- NeurIPS 2026LLM-Enhanced Random Forests in Orthogonal Hyperbolic Subspaces for Tabular Learning
- ICML 2026FedHPro: Federated Hyper-Prototype Learning via Gradient Matching
- NeurIPS 2025Feature-aware Modulation for Learning from Temporal Tabular Data
- ICML 2025TabFlex: Scaling Tabular Learning to Millions with Linear Attention
- ICLR 2025SAVA: Scalable Learning-Agnostic Data Valuation
- NeurIPS 2024Evaluating language models as risk scores
- ICML 2024Tabular Insights, Visual Impacts: Transferring Expertise from Tables to Images
全部表格深度学习论文
共 63 篇，第 2 / 2 页
- ICML 2023Personalized Federated Learning with Inferred Collaboration Graphs
- ICML 2023Quantitative Universal Approximation Bounds for Deep Belief Networks
- ICML 2023Robust Non-Linear Feedback Coding via Power-Constrained Deep Learning
- ICML 2023TabDDPM: Modelling Tabular Data with Diffusion Models
- ICML 2023TabLeak: Tabular Data Leakage in Federated Learning
- ICML 2023The Statistical Benefits of Quantile Temporal-Difference Learning for Value Estimation
- ICML 2023Towards Controlled Data Augmentations for Active Learning
- ICML 2023Towards Sustainable Learning: Coresets for Data-efficient Deep Learning
- ICML 2023Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning
- ICML 2023Trompt: Towards a Better Deep Neural Network for Tabular Data
- ICML 2023VA-learning as a more efficient alternative to Q-learning
- ICML 2023Variational Mixture of HyperGenerators for Learning Distributions over Functions
- ICML 2023XTab: Cross-table Pretraining for Tabular Transformers
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 查表格深度学习在 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": "tabular-deep-learning"}
常见问题
- 2023–2026 年四大会议一共有多少篇表格深度学习论文？
- 共 214 篇，按年份分别是 2023 年 150 篇、2024 年 17 篇、2025 年 14 篇、2026 年 33 篇。
- NeurIPS 2026 有多少篇表格深度学习论文？
- NeurIPS 2026 有 9 篇表格深度学习论文，上一届是 5 篇。
- ICLR 2026 有多少篇表格深度学习论文？
- ICLR 2026 有 1 篇表格深度学习论文，上一届是 6 篇。
- ICML 2026 有多少篇表格深度学习论文？
- ICML 2026 有 22 篇表格深度学习论文，上一届是 3 篇。
- CVPR 2026 有多少篇表格深度学习论文？
- CVPR 2026 有 1 篇表格深度学习论文。
- 哪个会议的表格深度学习论文最多？
- NeurIPS，2023–2026 年共 133 篇。