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

5,881 papers, page 111 of 118

5501. ICML 2023Exphormer: Sparse Transformers for Graphs
5502. ICML 2023Exponential Smoothing for Off-Policy Learning
5503. ICML 2023Extrapolated Random Tree for Regression
5504. ICML 2023Fast $(1+\varepsilon)$-Approximation Algorithms for Binary Matrix Factorization
5505. ICML 2023Fast Algorithms for Distributed k-Clustering with Outliers
5506. ICML 2023Fast Combinatorial Algorithms for Min Max Correlation Clustering
5507. ICML 2023Fast Rates for Maximum Entropy Exploration
5508. ICML 2023Federated Conformal Predictors for Distributed Uncertainty Quantification
5509. ICML 2023Few-bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction
5510. ICML 2023Fractional Denoising for 3D Molecular Pre-training
5511. ICML 2023Future-conditioned Unsupervised Pretraining for Decision Transformer
5512. ICML 2023Gaussian processes at the Helm(holtz): A more fluid model for ocean currents
5513. ICML 2023GC-Flow: A Graph-Based Flow Network for Effective Clustering
5514. ICML 2023GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models
5515. ICML 2023Generalization Analysis for Contrastive Representation Learning
5516. ICML 2023Generalized Teacher Forcing for Learning Chaotic Dynamics
5517. ICML 2023Generating Language Corrections for Teaching Physical Control Tasks
5518. ICML 2023GFlowNet-EM for Learning Compositional Latent Variable Models
5519. ICML 2023GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration
5520. ICML 2023Git-Theta: A Git Extension for Collaborative Development of Machine Learning Models
5521. ICML 2023Global optimality for Euclidean CCCP under Riemannian convexity
5522. ICML 2023GNN&GBDT-Guided Fast Optimizing Framework for Large-scale Integer Programming
5523. ICML 2023Gradient Descent Converges Linearly for Logistic Regression on Separable Data
5524. ICML 2023Gradient-based Wang--Landau Algorithm: A Novel Sampler for Output Distribution of Neural Networks over the Input Space
5525. ICML 2023Group Equivariant Fourier Neural Operators for Partial Differential Equations
5526. ICML 2023H-Likelihood Approach to Deep Neural Networks with Temporal-Spatial Random Effects for High-Cardinality Categorical Features
5527. ICML 2023Half-Hop: A graph upsampling approach for slowing down message passing
5528. ICML 2023Hiding Data Helps: On the Benefits of Masking for Sparse Coding
5529. ICML 2023High-dimensional Location Estimation via Norm Concentration for Subgamma Vectors
5530. ICML 2023How Jellyfish Characterise Alternating Group Equivariant Neural Networks
5531. ICML 2023How Powerful are Shallow Neural Networks with Bandlimited Random Weights?
5532. ICML 2023How to address monotonicity for model risk management?
5533. ICML 2023Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection
5534. ICML 2023Identifying Useful Learnwares for Heterogeneous Label Spaces
5535. ICML 2023Implicit Regularization Leads to Benign Overfitting for Sparse Linear Regression
5536. ICML 2023Improved Algorithms for Multi-period Multi-class Packing Problems with Bandit Feedback
5537. ICML 2023Improved Algorithms for White-Box Adversarial Streams
5538. ICML 2023Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation
5539. ICML 2023Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs
5540. ICML 2023Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Models
5541. ICML 2023Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics
5542. ICML 2023Interval Bound Interpolation for Few-shot Learning with Few Tasks
5543. ICML 2023Is Learning Summary Statistics Necessary for Likelihood-free Inference?
5544. ICML 2023Kernel Sufficient Dimension Reduction and Variable Selection for Compositional Data via Amalgamation
5545. ICML 2023Learning Affinity with Hyperbolic Representation for Spatial Propagation
5546. ICML 2023Learning Deep Time-index Models for Time Series Forecasting
5547. ICML 2023Likelihood Adjusted Semidefinite Programs for Clustering Heterogeneous Data
5548. ICML 2023Locally Regularized Neural Differential Equations: Some Black Boxes were meant to remain closed!
5549. ICML 2023LookupFFN: Making Transformers Compute-lite for CPU inference
5550. ICML 2023Looped Transformers as Programmable Computers

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.