Time Series papers, 2023–2026

Key findings

• Time Series went from 272 papers in 2023 to 876 in 2026, roughly 3.2x in three years.
• NeurIPS publishes the most Time Series work: 757 papers from 2023 to 2026, 35% of the four-venue total.
• The fastest-growing overlap is with Multimodal LLMs: papers tagged with both rose from 6 in 2023 to 85 in 2026.
• Among the 5 topics under Graph and Structured Data, it ranks #1 by 2026 paper count; the fastest grower in the group, Molecular Modeling, is up 2.7x versus 3.2x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Batched Hartigan's $k$-Means Clustering
• ICML 2026A Control-Theoretic View of Mamba on Stability and Robustness
• ICLR 2026A Single Architecture for Representing Invariance Under Any Space Group
• CVPR 2026Activation Matters Test-time Activated Negative Labels for OOD Detection with
• NeurIPS 2025Abstain Mask Retain Core: Time Series Prediction by Adaptive Masking Loss with Representation Consistency
• ICML 2025$K^2$VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting
• ICLR 2025A deep inverse-mapping model for a flapping robotic wing
• CVPR 2025Beyond Single-Modal Boundary: Cross-Modal Anomaly Detection through Visual Prototype and Harmonization
• NeurIPS 2024A Continuous-time Stochastic Gradient Descent Method for Continuous Data
• ICML 2024$S^2$IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
• ICLR 2024ARM: Refining Multivariate Forecasting with Adaptive Temporal-Contextual Learning
• CVPR 2024Each Test Image Deserves A Specific Prompt: Continual Test-Time Adaptation for 2D Medical Image Segmentation
• NeurIPS 2023A Sublinear-Time Spectral Clustering Oracle with Improved Preprocessing Time
• ICML 2023Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time
• ICLR 2023A Time Series is Worth 64 Words: Long-term Forecasting with Transformers
• CVPR 2023ActMAD: Activation Matching To Align Distributions for Test-Time-Training
• NeurIPS 2026A Locally Tokenized Generative Model for Robust Time-Series Watermarking
• ICML 2026ADHD Disease Detection Based on Short- and Long-Term Brain Function Encoding and Memory Graph Network
• ICLR 2026A Spectral-Grassmann Wasserstein metric for operator representations of dynamical systems
• CVPR 2026Continuous Exposure-Time Modeling for Realistic Atmospheric Turbulence Synthesis

All Time Series papers

2,156 papers, page 24 of 44

1151. ICML 2025Learning Time-Varying Multi-Region Brain Communications via Scalable Markovian Gaussian Processes
1152. ICML 2025Learning to (Learn at Test Time): RNNs with Expressive Hidden States
1153. ICML 2025Learning with Exact Invariances in Polynomial Time
1154. ICML 2025LETS Forecast: Learning Embedology for Time Series Forecasting
1155. ICML 2025LightGTS: A Lightweight General Time Series Forecasting Model
1156. ICML 2025Lightweight Online Adaption for Time Series Foundation Model Forecasts
1157. ICML 2025Linear Transformers as VAR Models: Aligning Autoregressive Attention Mechanisms with Autoregressive Forecasting
1158. ICML 2025LOB-Bench: Benchmarking Generative AI for Finance - an Application to Limit Order Book Data
1159. ICML 2025LSCD: Lomb--Scargle Conditioned Diffusion for Time series Imputation
1160. ICML 2025Masked Generative Nested Transformers with Decode Time Scaling
1161. ICML 2025Measuring In-Context Computation Complexity via Hidden State Prediction
1162. ICML 2025Mirror, Mirror of the Flow: How Does Regularization Shape Implicit Bias?
1163. ICML 2025Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts
1164. ICML 2025MTSTRec: Multimodal Time-Aligned Shared Token Recommender
1165. ICML 2025Non-stationary Diffusion For Probabilistic Time Series Forecasting
1166. ICML 2025Nonlinear transformers can perform inference-time feature learning
1167. ICML 2025Not All Tokens Matter All The Time: Dynamic Token Aggregation Towards Efficient Detection Transformers
1168. ICML 2025OmiAD: One-Step Adaptive Masked Diffusion Model for Multi-class Anomaly Detection via Adversarial Distillation
1169. ICML 2025Optimal Information Retention for Time-Series Explanations
1170. ICML 2025Optimization Proxies using Limited Labeled Data and Training Time -- A Semi-Supervised Bayesian Neural Network Approach
1171. ICML 2025Optimizing Language Models for Inference Time Objectives using Reinforcement Learning
1172. ICML 2025Patch-wise Structural Loss for Time Series Forecasting
1173. ICML 2025Polynomial Time Learning Augmented Algorithms for NP-hard Permutation Problems
1174. ICML 2025Polynomial-Time Approximability of Constrained Reinforcement Learning
1175. ICML 2025Portable Reward Tuning: Towards Reusable Fine-Tuning across Different Pretrained Models
1176. ICML 2025Position: It Is Time We Test Neural Computation In Vitro
1177. ICML 2025Privacy Amplification by Structured Subsampling for Deep Differentially Private Time Series Forecasting
1178. ICML 2025ProDiff: Prototype-Guided Diffusion for Minimal Information Trajectory Imputation
1179. ICML 2025Provable Length Generalization in Sequence Prediction via Spectral Filtering
1180. ICML 2025PTTA: Purifying Malicious Samples for Test-Time Model Adaptation
1181. ICML 2025Quantifying Memory Utilization with Effective State-Size
1182. ICML 2025Ranked Entropy Minimization for Continual Test-Time Adaptation
1183. ICML 2025Reinforcement Learning with Random Time Horizons
1184. ICML 2025Relational Conformal Prediction for Correlated Time Series
1185. ICML 2025Residual TPP: A Unified Lightweight Approach for Event Stream Data Analysis
1186. ICML 2025Rethinking Time Encoding via Learnable Transformation Functions
1187. ICML 2025Retrieval Augmented Time Series Forecasting
1188. ICML 2025Ringmaster ASGD: The First Asynchronous SGD with Optimal Time Complexity
1189. ICML 2025Risk and cross validation in ridge regression with correlated samples
1190. ICML 2025Robust Spatio-Temporal Centralized Interaction for OOD Learning
1191. ICML 2025Sample Complexity of Correlation Detection in the Gaussian Wigner Model
1192. ICML 2025Sample, Scrutinize and Scale: Effective Inference-Time Search by Scaling Verification
1193. ICML 2025SANA 1.5: Efficient Scaling of Training-Time and Inference-Time Compute in Linear Diffusion Transformer
1194. ICML 2025SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations
1195. ICML 2025SEAD: Unsupervised Ensemble of Streaming Anomaly Detectors
1196. ICML 2025Self-Bootstrapping for Versatile Test-Time Adaptation
1197. ICML 2025Shifting Time: Time-series Forecasting with Khatri-Rao Neural Operators
1198. ICML 2025SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting
1199. ICML 2025Slimming the Fat-Tail: Morphing-Flow for Adaptive Time Series Modeling
1200. ICML 2025SMART-PC: Skeletal Model Adaptation for Robust Test-Time Training in Point Clouds

FAQ

How many Time Series papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

2,157 in total: 272 in 2023, 424 in 2024, 585 in 2025, 876 in 2026.

How many Time Series papers are at NeurIPS 2026?

NeurIPS 2026 has 298 Time Series papers, versus 221 the year before.

How many Time Series papers are at ICLR 2026?

ICLR 2026 has 220 Time Series papers, versus 131 the year before.

How many Time Series papers are at ICML 2026?

ICML 2026 has 264 Time Series papers, versus 159 the year before.

How many Time Series papers are at CVPR 2026?

CVPR 2026 has 94 Time Series papers, versus 74 the year before.

Which conference publishes the most Time Series papers?

NeurIPS, with 757 papers from 2023 to 2026.