表格深度学习论文趋势 2023–2026

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。

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 133 篇，第 3 / 3 页

101. NeurIPS 2023Predicting a Protein's Stability under a Million Mutations
102. NeurIPS 2023ProteinShake: Building datasets and benchmarks for deep learning on protein structures
103. NeurIPS 2023Provable Advantage of Curriculum Learning on Parity Targets with Mixed Inputs
104. NeurIPS 2023QATCH: Benchmarking SQL-centric tasks with Table Representation Learning Models on Your Data
105. NeurIPS 2023REFINE: A Fine-Grained Medication Recommendation System Using Deep Learning and Personalized Drug Interaction Modeling
106. NeurIPS 2023Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark
107. NeurIPS 2023Retaining Beneficial Information from Detrimental Data for Neural Network Repair
108. NeurIPS 2023REx: Data-Free Residual Quantization Error Expansion
109. NeurIPS 2023Robust Learning with Progressive Data Expansion Against Spurious Correlation
110. NeurIPS 2023Scenario Diffusion: Controllable Driving Scenario Generation With Diffusion
111. NeurIPS 2023Self-Adaptive Motion Tracking against On-body Displacement of Flexible Sensors
112. NeurIPS 2023Smooth, exact rotational symmetrization for deep learning on point clouds
113. NeurIPS 2023SoTTA: Robust Test-Time Adaptation on Noisy Data Streams
114. NeurIPS 2023Sparse Deep Learning for Time Series Data: Theory and Applications
115. NeurIPS 2023Spectral Co-Distillation for Personalized Federated Learning
116. NeurIPS 2023StreamNet: Memory-Efficient Streaming Tiny Deep Learning Inference on the Microcontroller
117. NeurIPS 2023Supported Value Regularization for Offline Reinforcement Learning
118. NeurIPS 2023TabMT: Generating tabular data with masked transformers
119. NeurIPS 2023The Memory-Perturbation Equation: Understanding Model's Sensitivity to Data
120. NeurIPS 2023The Pursuit of Human Labeling: A New Perspective on Unsupervised Learning
121. NeurIPS 2023The Transient Nature of Emergent In-Context Learning in Transformers
122. NeurIPS 2023Tight Risk Bounds for Gradient Descent on Separable Data
123. NeurIPS 2023Toward Understanding Generative Data Augmentation
124. NeurIPS 2023Towards Data-Algorithm Dependent Generalization: a Case Study on Overparameterized Linear Regression
125. NeurIPS 2023Towards Free Data Selection with General-Purpose Models
126. NeurIPS 2023Towards Unbounded Machine Unlearning
127. NeurIPS 2023Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings
128. NeurIPS 2023Transportability for Bandits with Data from Different Environments
129. NeurIPS 2023Video Dynamics Prior: An Internal Learning Approach for Robust Video Enhancements
130. NeurIPS 2023Weakly Coupled Deep Q-Networks
131. NeurIPS 2023What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement.
132. NeurIPS 2023When Do Neural Nets Outperform Boosted Trees on Tabular Data?
133. NeurIPS 2023Zero-Shot Anomaly Detection via Batch Normalization

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。