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

2,111 papers, page 36 of 43

1751. NeurIPS 2024On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift
1752. NeurIPS 2024On the Power of Small-size Graph Neural Networks for Linear Programming
1753. NeurIPS 2024On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models
1754. NeurIPS 2024On Weak Regret Analysis for Dueling Bandits
1755. NeurIPS 2024Online Convex Optimisation: The Optimal Switching Regret for all Segmentations Simultaneously
1756. NeurIPS 2024OpenCDA-Loop: A Closed-loop Benchmarking Platform for End-to-end Evaluation of Cooperative Perception
1757. NeurIPS 2024OpenSatMap: A Fine-grained High-resolution Satellite Dataset for Large-scale Map Construction
1758. NeurIPS 2024Operator World Models for Reinforcement Learning
1759. NeurIPS 2024Optimal Algorithms for Augmented Testing of Discrete Distributions
1760. NeurIPS 2024Optimal Algorithms for Learning Partitions with Faulty Oracles
1761. NeurIPS 2024Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms
1762. NeurIPS 2024Optimal Scalarizations for Sublinear Hypervolume Regret
1763. NeurIPS 2024Optimal-state Dynamics Estimation for Physics-based Human Motion Capture from Videos
1764. NeurIPS 2024Oracle-Efficient Reinforcement Learning for Max Value Ensembles
1765. NeurIPS 2024Ordered Momentum for Asynchronous SGD
1766. NeurIPS 2024OT4P: Unlocking Effective Orthogonal Group Path for Permutation Relaxation
1767. NeurIPS 2024Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL
1768. NeurIPS 2024PAC-Bayes-Chernoff bounds for unbounded losses
1769. NeurIPS 2024PACE: Pacing Operator Learning to Accurate Optical Field Simulation for Complicated Photonic Devices
1770. NeurIPS 2024PaCE: Parsimonious Concept Engineering for Large Language Models
1771. NeurIPS 2024PaDeLLM-NER: Parallel Decoding in Large Language Models for Named Entity Recognition
1772. NeurIPS 2024Paloma: A Benchmark for Evaluating Language Model Fit
1773. NeurIPS 2024Parameter Competition Balancing for Model Merging
1774. NeurIPS 2024Parameterized Approximation Schemes for Fair-Range Clustering
1775. NeurIPS 2024Pearls from Pebbles: Improved Confidence Functions for Auto-labeling
1776. NeurIPS 2024Periodic agent-state based Q-learning for POMDPs
1777. NeurIPS 2024Perplexity-aware Correction for Robust Alignment with Noisy Preferences
1778. NeurIPS 2024Persistent Homology for High-dimensional Data Based on Spectral Methods
1779. NeurIPS 2024PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs
1780. NeurIPS 2024Policy Optimization for Robust Average Reward MDPs
1781. NeurIPS 2024Practical $0.385$-Approximation for Submodular Maximization Subject to a Cardinality Constraint
1782. NeurIPS 2024Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks
1783. NeurIPS 2024Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs
1784. NeurIPS 2024Progressive Exploration-Conformal Learning for Sparsely Annotated Object Detection in Aerial Images
1785. NeurIPS 2024PROSPECT PTMs: Rich Labeled Tandem Mass Spectrometry Dataset of Modified Peptides for Machine Learning in Proteomics
1786. NeurIPS 2024Prospective Learning: Learning for a Dynamic Future
1787. NeurIPS 2024Prospective Representation Learning for Non-Exemplar Class-Incremental Learning
1788. NeurIPS 2024Provable Benefits of Complex Parameterizations for Structured State Space Models
1789. NeurIPS 2024PTQ4DiT: Post-training Quantization for Diffusion Transformers
1790. NeurIPS 2024PV-Tuning: Beyond Straight-Through Estimation for Extreme LLM Compression
1791. NeurIPS 2024Q-Distribution guided Q-learning for offline reinforcement learning: Uncertainty penalized Q-value via consistency model
1792. NeurIPS 2024QBB: Quantization with Binary Bases for LLMs
1793. NeurIPS 2024QGym: Scalable Simulation and Benchmarking of Queuing Network Controllers
1794. NeurIPS 2024Quantum Deep Equilibrium Models
1795. NeurIPS 2024RClicks: Realistic Click Simulation for Benchmarking Interactive Segmentation
1796. NeurIPS 2024RedPajama: an Open Dataset for Training Large Language Models
1797. NeurIPS 2024ReF-LDM: A Latent Diffusion Model for Reference-based Face Image Restoration
1798. NeurIPS 2024Regularized Adaptive Momentum Dual Averaging with an Efficient Inexact Subproblem Solver for Training Structured Neural Network
1799. NeurIPS 2024Reimagining Mutual Information for Enhanced Defense against Data Leakage in Collaborative Inference
1800. NeurIPS 2024RelBench: A Benchmark for Deep Learning on Relational Databases

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.