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

358 papers, page 7 of 8

301. ICML 2024RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation
302. ICML 2024Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination
303. ICML 2024Robustness of Deep Learning for Accelerated MRI: Benefits of Diverse Training Data
304. ICML 2024Sample Complexity Bounds for Estimating Probability Divergences under Invariances
305. ICML 2024Sample-specific Masks for Visual Reprogramming-based Prompting
306. ICML 2024Sampling is as easy as keeping the consistency: convergence guarantee for Consistency Models
307. ICML 2024Scaling Laws for the Value of Individual Data Points in Machine Learning
308. ICML 2024Seesaw: Compensating for Nonlinear Reduction with Linear Computations for Private Inference
309. ICML 2024Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs
310. ICML 2024Simple Ingredients for Offline Reinforcement Learning
311. ICML 2024Simulation of Graph Algorithms with Looped Transformers
312. ICML 2024Simulation-Based Inference with Quantile Regression
313. ICML 2024SiT: Symmetry-invariant Transformers for Generalisation in Reinforcement Learning
314. ICML 2024Slicing Mutual Information Generalization Bounds for Neural Networks
315. ICML 2024SPADE: Sparsity-Guided Debugging for Deep Neural Networks
316. ICML 2024Sparse-IFT: Sparse Iso-FLOP Transformations for Maximizing Training Efficiency
317. ICML 2024Spectral Preconditioning for Gradient Methods on Graded Non-convex Functions
318. ICML 2024Spider: A Unified Framework for Context-dependent Concept Segmentation
319. ICML 2024Spike Distance Function as a Learning Objective for Spike Prediction
320. ICML 2024SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN
321. ICML 2024Stochastic Q-learning for Large Discrete Action Spaces
322. ICML 2024Stop Regressing: Training Value Functions via Classification for Scalable Deep RL
323. ICML 2024Submodular framework for structured-sparse optimal transport
324. ICML 2024Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation
325. ICML 2024SyCoCa: Symmetrizing Contrastive Captioners with Attentive Masking for Multimodal Alignment
326. ICML 2024Tandem Transformers for Inference Efficient LLMs
327. ICML 2024Taylor Videos for Action Recognition
328. ICML 2024TENG: Time-Evolving Natural Gradient for Solving PDEs With Deep Neural Nets Toward Machine Precision
329. ICML 2024TERD: A Unified Framework for Safeguarding Diffusion Models Against Backdoors
330. ICML 2024The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents
331. ICML 2024The Merit of River Network Topology for Neural Flood Forecasting
332. ICML 2024Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians
333. ICML 2024Thermometer: Towards Universal Calibration for Large Language Models
334. ICML 2024TIC-TAC: A Framework For Improved Covariance Estimation In Deep Heteroscedastic Regression
335. ICML 2024Total Variation Floodgate for Variable Importance Inference in Classification
336. ICML 2024Towards Certified Unlearning for Deep Neural Networks
337. ICML 2024Towards Realistic Model Selection for Semi-supervised Learning
338. ICML 2024Trainable Transformer in Transformer
339. ICML 2024Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning
340. ICML 2024Triple Changes Estimator for Targeted Policies
341. ICML 2024Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning
342. ICML 2024Trust Regions for Explanations via Black-Box Probabilistic Certification
343. ICML 2024TSLANet: Rethinking Transformers for Time Series Representation Learning
344. ICML 2024Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation
345. ICML 2024ULAREF: A Unified Label Refinement Framework for Learning with Inaccurate Supervision
346. ICML 2024Uncertainty for Active Learning on Graphs
347. ICML 2024Unveiling the Potential of AI for Nanomaterial Morphology Prediction
348. ICML 2024Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models
349. ICML 2024Variational Inference with Coverage Guarantees in Simulation-Based Inference
350. ICML 2024Variational Learning is Effective for Large Deep Networks

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.