Tabular Deep Learning papers, 2023–2026

Key findings

• Tabular Deep Learning fell from 150 papers in 2023 to 33 in 2026, so interest is cooling.
• NeurIPS publishes the most Tabular Deep Learning work: 133 papers from 2023 to 2026, 62% of the four-venue total.
• The fastest-growing overlap is with Simulation for Driving: papers tagged with both rose from 3 in 2023 to 6 in 2026.
• Among the 5 topics under Graph and Structured Data, it ranks #5 by 2026 paper count; the fastest grower in the group, Time Series, is up 3.2x versus 0.2x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All Tabular Deep Learning papers

214 papers, page 4 of 5

151. NeurIPS 2023HyTrel: Hypergraph-enhanced Tabular Data Representation Learning
152. NeurIPS 2023Implicit Bias of Gradient Descent for Two-layer ReLU and Leaky ReLU Networks on Nearly-orthogonal Data
153. NeurIPS 2023Integration-free Training for Spatio-temporal Multimodal Covariate Deep Kernel Point Processes
154. NeurIPS 2023Joint Data-Task Generation for Auxiliary Learning
155. NeurIPS 2023Joint Training of Deep Ensembles Fails Due to Learner Collusion
156. NeurIPS 2023Labeling Neural Representations with Inverse Recognition
157. NeurIPS 2023Language Models are Weak Learners
158. NeurIPS 2023Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering
159. NeurIPS 2023LithoBench: Benchmarking AI Computational Lithography for Semiconductor Manufacturing
160. NeurIPS 2023Meet in the Middle: A New Pre-training Paradigm
161. NeurIPS 2023Mitigating the Effect of Incidental Correlations on Part-based Learning
162. NeurIPS 2023NCDL: A Framework for Deep Learning on non-Cartesian Lattices
163. NeurIPS 2023New Bounds for Hyperparameter Tuning of Regression Problems Across Instances
164. NeurIPS 2023Noether Embedding: Efficient Learning of Temporal Regularities
165. NeurIPS 2023Offline Imitation Learning with Variational Counterfactual Reasoning
166. NeurIPS 2023On Class Distributions Induced by Nearest Neighbor Graphs for Node Classification of Tabular Data
167. NeurIPS 2023On Imitation in Mean-field Games
168. NeurIPS 2023On Single-Index Models beyond Gaussian Data
169. NeurIPS 2023On the Convergence of No-Regret Learning Dynamics in Time-Varying Games
170. NeurIPS 2023On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets
171. NeurIPS 2023On the Overlooked Structure of Stochastic Gradients
172. NeurIPS 2023On the Robustness of Removal-Based Feature Attributions
173. NeurIPS 2023On the Role of Randomization in Adversarially Robust Classification
174. NeurIPS 2023One-Pass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning
175. NeurIPS 2023OpenDataVal: a Unified Benchmark for Data Valuation
176. NeurIPS 2023Operator Learning with Neural Fields: Tackling PDEs on General Geometries
177. NeurIPS 2023Optimize Planning Heuristics to Rank, not to Estimate Cost-to-Goal
178. NeurIPS 2023PAC Learning Linear Thresholds from Label Proportions
179. NeurIPS 2023Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck
180. NeurIPS 2023Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control
181. NeurIPS 2023Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds
182. NeurIPS 2023Predicting a Protein's Stability under a Million Mutations
183. NeurIPS 2023ProteinShake: Building datasets and benchmarks for deep learning on protein structures
184. NeurIPS 2023Provable Advantage of Curriculum Learning on Parity Targets with Mixed Inputs
185. NeurIPS 2023QATCH: Benchmarking SQL-centric tasks with Table Representation Learning Models on Your Data
186. NeurIPS 2023REFINE: A Fine-Grained Medication Recommendation System Using Deep Learning and Personalized Drug Interaction Modeling
187. NeurIPS 2023Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark
188. NeurIPS 2023Retaining Beneficial Information from Detrimental Data for Neural Network Repair
189. NeurIPS 2023REx: Data-Free Residual Quantization Error Expansion
190. NeurIPS 2023Robust Learning with Progressive Data Expansion Against Spurious Correlation
191. NeurIPS 2023Scenario Diffusion: Controllable Driving Scenario Generation With Diffusion
192. NeurIPS 2023Self-Adaptive Motion Tracking against On-body Displacement of Flexible Sensors
193. NeurIPS 2023Smooth, exact rotational symmetrization for deep learning on point clouds
194. NeurIPS 2023SoTTA: Robust Test-Time Adaptation on Noisy Data Streams
195. NeurIPS 2023Sparse Deep Learning for Time Series Data: Theory and Applications
196. NeurIPS 2023Spectral Co-Distillation for Personalized Federated Learning
197. NeurIPS 2023StreamNet: Memory-Efficient Streaming Tiny Deep Learning Inference on the Microcontroller
198. NeurIPS 2023Supported Value Regularization for Offline Reinforcement Learning
199. NeurIPS 2023TabMT: Generating tabular data with masked transformers
200. NeurIPS 2023The Memory-Perturbation Equation: Understanding Model's Sensitivity to Data

FAQ

How many Tabular Deep Learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

214 in total: 150 in 2023, 17 in 2024, 14 in 2025, 33 in 2026.

How many Tabular Deep Learning papers are at NeurIPS 2026?

NeurIPS 2026 has 9 Tabular Deep Learning papers, versus 5 the year before.

How many Tabular Deep Learning papers are at ICLR 2026?

ICLR 2026 has 1 Tabular Deep Learning papers, versus 6 the year before.

How many Tabular Deep Learning papers are at ICML 2026?

ICML 2026 has 22 Tabular Deep Learning papers, versus 3 the year before.

How many Tabular Deep Learning papers are at CVPR 2026?

CVPR 2026 has 1 Tabular Deep Learning papers.

Which conference publishes the most Tabular Deep Learning papers?

NeurIPS, with 133 papers from 2023 to 2026.