Simulation for Driving papers, 2023–2026
Closed-loop simulation
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 5,882 papers are tagged with this topic.
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.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 219 | 182 | 218 | 350 | 969 |
| 2024 | 410 | 176 | 358 | 364 | 1,308 |
| 2025 | 542 | 228 | 275 | 360 | 1,405 |
| 2026 | 940 | 313 | 363 | 584 | 2,200 |
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
1,405 papers, page 15 of 29
- ICML 2025HyperIMTS: Hypergraph Neural Network for Irregular Multivariate Time Series Forecasting
- ICML 2025Hyperspherical Normalization for Scalable Deep Reinforcement Learning
- ICML 2025Hypothesis Testing for Generalized Thurstone Models
- ICML 2025Implicit Bias of Gradient Descent for Non-Homogeneous Deep Networks
- ICML 2025Implicit Regularization for Tubal Tensor Factorizations via Gradient Descent
- ICML 2025Importance Sampling for Nonlinear Models
- ICML 2025Improved Algorithm for Deep Active Learning under Imbalance via Optimal Separation
- ICML 2025Improved Learning via k-DTW: A Novel Dissimilarity Measure for Curves
- ICML 2025Improved Online Confidence Bounds for Multinomial Logistic Bandits
- ICML 2025Improving Memory Efficiency for Training KANs via Meta Learning
- ICML 2025Independence Tests for Language Models
- ICML 2025Inductive Gradient Adjustment for Spectral Bias in Implicit Neural Representations
- ICML 2025Info-Coevolution: An Efficient Framework for Data Model Coevolution
- ICML 2025INRFlow: Flow Matching for INRs in Ambient Space
- ICML 2025Instance-Optimal Pure Exploration for Linear Bandits on Continuous Arms
- ICML 2025Instruction-Following Pruning for Large Language Models
- ICML 2025Integration-free Kernels for Equivariant Gaussian Process Modelling
- ICML 2025Interpolating Neural Network-Tensor Decomposition (INN-TD): a scalable and interpretable approach for large-scale physics-based problems
- ICML 2025K$^2$IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes
- ICML 2025KoNODE: Koopman-Driven Neural Ordinary Differential Equations with Evolving Parameters for Time Series Analysis
- ICML 2025Label Distribution Propagation-based Label Completion for Crowdsourcing
- ICML 2025Ladder-Residual: Parallelism-Aware Architecture for Accelerating Large Model Inference with Communication Overlapping
- ICML 2025Large Language Model-driven Large Neighborhood Search for Large-Scale MILP Problems
- ICML 2025Large Language Models are Demonstration Pre-Selectors for Themselves
- ICML 2025Larger or Smaller Reward Margins to Select Preferences for LLM Alignment?
- ICML 2025LARM: Large Auto-Regressive Model for Long-Horizon Embodied Intelligence
- ICML 2025Latent Score-Based Reweighting for Robust Classification on Imbalanced Tabular Data
- ICML 2025Learning from Sample Stability for Deep Clustering
- ICML 2025Learning Input Encodings for Kernel-Optimal Implicit Neural Representations
- ICML 2025Learning Representations of Instruments for Partial Identification of Treatment Effects
- ICML 2025Learning State-Based Node Representations from a Class Hierarchy for Fine-Grained Open-Set Detection
- ICML 2025Learning to Generate Projections for Reducing Dimensionality of Heterogeneous Linear Programming Problems
- ICML 2025Learning to Quantize for Training Vector-Quantized Networks
- ICML 2025Learning to Stop: Deep Learning for Mean Field Optimal Stopping
- ICML 2025Learning without Isolation: Pathway Protection for Continual Learning
- ICML 2025Learning-Augmented Algorithms for MTS with Bandit Access to Multiple Predictors
- ICML 2025LETS Forecast: Learning Embedology for Time Series Forecasting
- ICML 2025LEVIS: Large Exact Verifiable Input Spaces for Neural Networks
- ICML 2025LGDM: Latent Guidance in Diffusion Models for Perceptual Evaluations
- ICML 2025Linear convergence of Sinkhorn's algorithm for generalized static Schrödinger bridge
- ICML 2025LineFlow: A Framework to Learn Active Control of Production Lines
- ICML 2025Logits are All We Need to Adapt Closed Models
- ICML 2025LSCD: Lomb--Scargle Conditioned Diffusion for Time series Imputation
- ICML 2025MARS: Unleashing the Power of Variance Reduction for Training Large Models
- ICML 2025Masked Autoencoders Are Effective Tokenizers for Diffusion Models
- ICML 2025MERGE$^3$: Efficient Evolutionary Merging on Consumer-grade GPUs
- ICML 2025MERIT: Maximum-normalized Element-wise Ratio for Language Model Large-batch Training
- ICML 2025Meta Optimality for Demographic Parity Constrained Regression via Post-Processing
- ICML 2025Minimum Width for Universal Approximation using Squashable Activation Functions
- ICML 2025Multi-Marginal Stochastic Flow Matching for High-Dimensional Snapshot Data at Irregular Time Points
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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.