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

264 papers, page 4 of 6

151. ICML 2026NaviCache: Test-Time Self-Calibration Caching for Video Generation
152. ICML 2026Nested birth-death processes are competitive with neural networks as time-dependent models of protein evolution
153. ICML 2026Nested Spatio-Temporal Time Series Forecasting
154. ICML 2026Neural Modular Physics for Elastic Simulation
155. ICML 2026NeurOCNN: A Neural-Operator-Based Model for Physiological Time Series
156. ICML 2026Noise-Robust Density Estimation for Tabular Data Anomaly Detection
157. ICML 2026Normality Calibration in Semi-supervised Graph Anomaly Detection
158. ICML 2026Not All Frequencies Are Equal: Energy-Adaptive Diffusion for Time Series Forecasting
159. ICML 2026Olivia: Harmonizing Time Series Foundation Models with Power Spectral Density
160. ICML 2026On Structured State-Space Duality
161. ICML 2026On the "Induction Bias" in Sequence Models
162. ICML 2026On the Learnability of Test-Time Adaptation: A Recovery Complexity Perspective
163. ICML 2026On the Limits of Test-Time Compute: Sequential Reward Filtering for Better Inference
164. ICML 2026On the Power of (Approximate) Reward Models for Inference-Time Scaling: Sequential Monte Carlo and Beyond
165. ICML 2026Once-for-All: Scalable Simultaneous Forecasting via Equilibrium State Estimation
166. ICML 2026One Batch Is Enough: A Unified Dataset Condensation Framework for General Time Series Analysis
167. ICML 2026One-Step Graph-Structured Neural Flows for Irregular Multivariate Time Series Classification
168. ICML 2026Online Change Point Detection for Multivariate Inhomogeneous Poisson Processes Time Series
169. ICML 2026OpenTSLM: Time-Series Language Models for Reasoning over Multivariate Medical Text- and Time-Series Data
170. ICML 2026Optimizing Inference-Time Compute for Medical Reasoning via Uncertainty Quantification
171. ICML 2026Optimizing Network Simulation: Enhancing Performance Prediction Accuracy via Neural Architecture Search
172. ICML 2026OSM+: Billion-Level Open Street Map Dataset for City-wide Experiments
173. ICML 2026Overcoming the Modality Gap in Context-Aided Forecasting
174. ICML 2026ParalESN: Enabling parallel information processing in Reservoir Computing
175. ICML 2026Parameter Decorrelation via Transition-Variance Alignment for Multivariate Time-series Forecasting
176. ICML 2026Parameter-free Dynamic Regret: Time-varying Movement Costs, Delayed Feedback, and Memory
177. ICML 2026Parametric Prior Mapping Framework for Non-stationary Probabilistic Time Series Forecasting
178. ICML 2026PATRA: Pattern-Aware Alignment and Balanced Reasoning for Time Series Question Answering
179. ICML 2026PESD-TSF: A Period-Aware and Explicit Structured Decomposition Framework for Long-Term Time Series Forecasting
180. ICML 2026PLASH: Provably Linear-Time Attention with Selective Higher-Order Feature Sketching
181. ICML 2026PolicyGuard: Towards Test-time and Step-level Adversary Defense for Reinforcement Learning Agent
182. ICML 2026Power-Boosted Granger-Causal Discovery for Large Heterogeneous Panel Data
183. ICML 2026PRISM: Training-Free Video Anomaly Detection via Intrinsic Statistical Modeling
184. ICML 2026Privately Fine-Tuned LLMs Preserve Temporal Dynamics in Tabular Data
185. ICML 2026ProSAR: Prototype-Guided Semantic Augmentation and Refinement for Time Series Contrastive Learning
186. ICML 2026PULSE: Generative Phase Evolution for Non-Stationary Time Series Forecasting
187. ICML 2026QuITE: Query-Based Irregular Time Series Embedding
188. ICML 2026Ranking Time Series using a Time Warping Ideal Point Model
189. ICML 2026Re-FORC: Adaptive Reward Prediction for Efficient Chain-of-Thought Reasoning
190. ICML 2026RealtimeTool: Parallel Decoding for Real-Time LLM Function Calling
191. ICML 2026ReAugment: Targeted Few-Shot Time Series Augmentation via Model Zoo-Guided Reinforcement Learning
192. ICML 2026ReNF: Rethinking the Design of Neural Long-Term Time Series Forecasters
193. ICML 2026Residual-Guided Multi-Resolution Refinement of Foundation Models: A Case Study in Drought Forecasting
194. ICML 2026Rethinking Efficient Graph Coarsening via a Non-Selfishness Principle
195. ICML 2026Rethinking Multimodal Time-Series Forecasting Evaluation
196. ICML 2026Rethinking Time-Series Imputation as Conditional Inference along Temporal Evolution
197. ICML 2026Revealing Scaling Paradox in Large-scale Time Series Models: Implications for More Efficient and Accurate Forecasting
198. ICML 2026Revisiting Neural Processes via Fourier Transform and Volterra Series
199. ICML 2026Reviving Error Correction in Modern Deep Time-Series Forecasting
200. ICML 2026Robust Causal Discovery in Real-World Time Series with Power-Laws

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.