Simulation for Driving papers, 2023–2026

Key findings

• Simulation for Driving went from 969 papers in 2023 to 2,200 in 2026, roughly 2.3x in three years.
• NeurIPS publishes the most Simulation for Driving work: 2,111 papers from 2023 to 2026, 36% of the four-venue total.
• The fastest-growing overlap is with Diffusion Models: papers tagged with both rose from 27 in 2023 to 205 in 2026.
• Among the 5 topics under Autonomous Driving, it ranks #1 by 2026 paper count; the fastest grower in the group, Motion Planning, is up 2.4x versus 2.3x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026$SE(2)$-Aware Conditional Distribution Transport for Vehicle Trajectory Generation
• ICML 2026A Penalty Approach For Differentiation Through Black-box Quadratic Programming Solvers
• ICLR 2026A Schrödinger Eigenfunction Method for Long-Horizon Stochastic Optimal Control
• CVPR 2026A2GC Asymmetric Aggregation with Geometric Constraints for Locally Aggregated Descriptors
• NeurIPS 2025A compressive-expressive communication framework for compositional representations
• ICML 2025A Near-Optimal Single-Loop Stochastic Algorithm for Convex Finite-Sum Coupled Compositional Optimization
• ICLR 2025A Truncated Newton Method for Optimal Transport
• CVPR 20253D-SLNR: A Super Lightweight Neural Representation for Large-scale 3D Mapping
• NeurIPS 2024[Re] CUDA: Curriculum of Data Augmentation for Long‐tailed Recognition
• ICML 2024$H$-Consistency Guarantees for Regression
• ICLR 2024$\texttt{NAISR}$: A 3D Neural Additive Model for Interpretable Shape Representation
• CVPR 2024Decentralized Directed Collaboration for Personalized Federated Learning
• NeurIPS 2023[Re] FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles
• ICML 2023$H$-Consistency Bounds for Pairwise Misranking Loss Surrogates
• ICLR 2023A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data
• CVPR 20233DAvatarGAN: Bridging Domains for Personalized Editable Avatars
• NeurIPS 2026A Bitter Lesson for Data Filtering
• ICML 2026A Queueing-Theoretic Framework for Stability Analysis of LLM Inference with KV Cache Memory Constraints
• ICLR 2026Bayesian Neural Networks for Functional ANOVA Model
• CVPR 2026Active Perceptual Inference A Corticothalamic-Inspired Dynamic Nested Recurrent Network for

All Simulation for Driving papers

1,214 papers, page 23 of 25

1101. ICML 2023LookupFFN: Making Transformers Compute-lite for CPU inference
1102. ICML 2023Looped Transformers as Programmable Computers
1103. ICML 2023Loss Balancing for Fair Supervised Learning
1104. ICML 2023Low Complexity Homeomorphic Projection to Ensure Neural-Network Solution Feasibility for Optimization over (Non-)Convex Set
1105. ICML 2023LSDS++ : Dual Sampling for Accelerated k-means++
1106. ICML 2023Memory-Based Dual Gaussian Processes for Sequential Learning
1107. ICML 2023Mixing Predictions for Online Metric Algorithms
1108. ICML 2023Model-Bellman Inconsistency for Model-based Offline Reinforcement Learning
1109. ICML 2023ModelDiff: A Framework for Comparing Learning Algorithms
1110. ICML 2023Monotonic Location Attention for Length Generalization
1111. ICML 2023MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks
1112. ICML 2023Multicalibration as Boosting for Regression
1113. ICML 2023Multiple Thinking Achieving Meta-Ability Decoupling for Object Navigation
1114. ICML 2023Multiplier Bootstrap-based Exploration
1115. ICML 2023MyoDex: A Generalizable Prior for Dexterous Manipulation
1116. ICML 2023Near-Optimal Quantum Coreset Construction Algorithms for Clustering
1117. ICML 2023Nearly Minimax Optimal Regret for Learning Linear Mixture Stochastic Shortest Path
1118. ICML 2023Nearly-Optimal Hierarchical Clustering for Well-Clustered Graphs
1119. ICML 2023Nested Elimination: A Simple Algorithm for Best-Item Identification From Choice-Based Feedback
1120. ICML 2023Neural Inverse Operators for Solving PDE Inverse Problems
1121. ICML 2023Neural Wasserstein Gradient Flows for Discrepancies with Riesz Kernels
1122. ICML 2023NNSplitter: An Active Defense Solution for DNN Model via Automated Weight Obfuscation
1123. ICML 2023Nonparametric Extensions of Randomized Response for Private Confidence Sets
1124. ICML 2023Normalizing Flows for Interventional Density Estimation
1125. ICML 2023OMS-DPM: Optimizing the Model Schedule for Diffusion Probabilistic Models
1126. ICML 2023On Coresets for Clustering in Small Dimensional Euclidean spaces
1127. ICML 2023On Kinetic Optimal Probability Paths for Generative Models
1128. ICML 2023On Pre-Training for Visuo-Motor Control: Revisiting a Learning-from-Scratch Baseline
1129. ICML 2023On Provable Copyright Protection for Generative Models
1130. ICML 2023On Second-Order Scoring Rules for Epistemic Uncertainty Quantification
1131. ICML 2023On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters
1132. ICML 2023One-Step Estimator for Permuted Sparse Recovery
1133. ICML 2023Optimal Convergence Rates for Agnostic Nyström Kernel Learning
1134. ICML 2023Optimal No-Regret Learning for One-Sided Lipschitz Functions
1135. ICML 2023Optimal randomized multilevel Monte Carlo for repeatedly nested expectations
1136. ICML 2023Optimally-weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference
1137. ICML 2023Optimizing Mode Connectivity for Class Incremental Learning
1138. ICML 2023Over-parametrization via Lifting for Low-rank Matrix Sensing: Conversion of Spurious Solutions to Strict Saddle Points
1139. ICML 2023Parameter-Level Soft-Masking for Continual Learning
1140. ICML 2023Patch-level Contrastive Learning via Positional Query for Visual Pre-training
1141. ICML 2023Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks
1142. ICML 2023Phase-aware Adversarial Defense for Improving Adversarial Robustness
1143. ICML 2023Polynomial Preconditioning for Gradient Methods
1144. ICML 2023Predictable MDP Abstraction for Unsupervised Model-Based RL
1145. ICML 2023Predictive Flows for Faster Ford-Fulkerson
1146. ICML 2023Probabilistic Attention-to-Influence Neural Models for Event Sequences
1147. ICML 2023Progressive Purification for Instance-Dependent Partial Label Learning
1148. ICML 2023Projected Tensor Power Method for Hypergraph Community Recovery
1149. ICML 2023Prompting Large Language Model for Machine Translation: A Case Study
1150. ICML 2023Proper Losses for Discrete Generative Models

FAQ

How many Simulation for Driving papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

5,882 in total: 969 in 2023, 1,308 in 2024, 1,405 in 2025, 2,200 in 2026.

How many Simulation for Driving papers are at NeurIPS 2026?

NeurIPS 2026 has 940 Simulation for Driving papers, versus 542 the year before.

How many Simulation for Driving papers are at ICLR 2026?

ICLR 2026 has 313 Simulation for Driving papers, versus 228 the year before.

How many Simulation for Driving papers are at ICML 2026?

ICML 2026 has 363 Simulation for Driving papers, versus 275 the year before.

How many Simulation for Driving papers are at CVPR 2026?

CVPR 2026 has 584 Simulation for Driving papers, versus 360 the year before.

Which conference publishes the most Simulation for Driving papers?

NeurIPS, with 2,111 papers from 2023 to 2026.