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
2,111 papers, page 38 of 43
- NeurIPS 2024Take A Shortcut Back: Mitigating the Gradient Vanishing for Training Spiking Neural Networks
- NeurIPS 2024TFG: Unified Training-Free Guidance for Diffusion Models
- NeurIPS 2024TFS-NeRF: Template-Free NeRF for Semantic 3D Reconstruction of Dynamic Scene
- NeurIPS 2024The Fine-Grained Complexity of Gradient Computation for Training Large Language Models
- NeurIPS 2024The Minimax Rate of HSIC Estimation for Translation-Invariant Kernels
- NeurIPS 2024The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning
- NeurIPS 2024Theoretical guarantees in KL for Diffusion Flow Matching
- NeurIPS 2024Tight Bounds for Learning RUMs from Small Slates
- NeurIPS 2024Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective
- NeurIPS 2024TinyLUT: Tiny Look-Up Table for Efficient Image Restoration at the Edge
- NeurIPS 2024To Believe or Not to Believe Your LLM: Iterative Prompting for Estimating Epistemic Uncertainty
- NeurIPS 2024Tolerant Algorithms for Learning with Arbitrary Covariate Shift
- NeurIPS 2024TopoLogic: An Interpretable Pipeline for Lane Topology Reasoning on Driving Scenes
- NeurIPS 2024Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
- NeurIPS 2024Toward Efficient Inference for Mixture of Experts
- NeurIPS 2024Towards Universal Mesh Movement Networks
- NeurIPS 2024Toxicity Detection for Free
- NeurIPS 2024Trading Place for Space: Increasing Location Resolution Reduces Contextual Capacity in Hippocampal Codes
- NeurIPS 2024Transfer Learning for Latent Variable Network Models
- NeurIPS 2024Transfer Q-star : Principled Decoding for LLM Alignment
- NeurIPS 2024Typicalness-Aware Learning for Failure Detection
- NeurIPS 2024Unified Domain Generalization and Adaptation for Multi-View 3D Object Detection
- NeurIPS 2024UniMTS: Unified Pre-training for Motion Time Series
- NeurIPS 2024UniSDF: Unifying Neural Representations for High-Fidelity 3D Reconstruction of Complex Scenes with Reflections
- NeurIPS 2024Universal Exact Compression of Differentially Private Mechanisms
- NeurIPS 2024Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators
- NeurIPS 2024Universal Rates for Active Learning
- NeurIPS 2024Universal Sample Coding
- NeurIPS 2024Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models
- NeurIPS 2024UrbanDataLayer: A Unified Data Pipeline for Urban Science
- NeurIPS 2024Validating Climate Models with Spherical Convolutional Wasserstein Distance
- NeurIPS 2024Vector Quantization Prompting for Continual Learning
- NeurIPS 2024Wasserstein convergence of Cech persistence diagrams for samplings of submanifolds
- NeurIPS 2024Wasserstein Distance Rivals Kullback-Leibler Divergence for Knowledge Distillation
- NeurIPS 2024What Is Missing For Graph Homophily? Disentangling Graph Homophily For Graph Neural Networks
- NeurIPS 2024What Makes CLIP More Robust to Long-Tailed Pre-Training Data? A Controlled Study for Transferable Insights
- NeurIPS 2024WindsorML: High-Fidelity Computational Fluid Dynamics Dataset For Automotive Aerodynamics
- NeurIPS 2024Wormhole Loss for Partial Shape Matching
- NeurIPS 2024xMIL: Insightful Explanations for Multiple Instance Learning in Histopathology
- NeurIPS 2024You Only Cache Once: Decoder-Decoder Architectures for Language Models
- NeurIPS 2024Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion
- NeurIPS 2024ZOPP: A Framework of Zero-shot Offboard Panoptic Perception for Autonomous Driving
- NeurIPS 2023[Re] FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles
- NeurIPS 2023$S^3$: Increasing GPU Utilization during Generative Inference for Higher Throughput
- NeurIPS 2023A Bounded Ability Estimation for Computerized Adaptive Testing
- NeurIPS 2023A Dataset for Analyzing Streaming Media Performance over HTTP/3 Browsers
- NeurIPS 2023A Finite-Particle Convergence Rate for Stein Variational Gradient Descent
- NeurIPS 2023A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning
- NeurIPS 2023A Riemannian Exponential Augmented Lagrangian Method for Computing the Projection Robust Wasserstein Distance
- NeurIPS 2023A Robust Exact Algorithm for the Euclidean Bipartite Matching Problem
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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.