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

298 papers, page 3 of 6

101. NeurIPS 2026FracTS: Hierarchical and Autoregressive Time Series Generation
102. NeurIPS 2026From Cortical Synchronous Rhythm to Brain Inspired Learning Mechanism: An Oscillatory Spiking Neural Network with Time-Delayed Coordination
103. NeurIPS 2026From Post-Hoc to Ante-Hoc: Consistently Explainable Semi-Supervised Time Series Classification
104. NeurIPS 2026Full-Atom Cyclic Peptide Design via Test-Time Scaled Autoregressive Flow Matching
105. NeurIPS 2026GAPS: Gradient-Aware Adaptation-Gap Scoring for Time-Series Anomaly Detection with Foundation Models
106. NeurIPS 2026Generating Financial Time Series by Matching Random Convolutional Features
107. NeurIPS 2026GeoWind2Plan: Mission-Time 3D Urban Wind Prediction for Energy-Efficient UAV Planning
108. NeurIPS 2026HARMONY: Hierarchical Anchor Retrieval on Manifold for Oblivious-source Acoustic Anomaly Detection
109. NeurIPS 2026Hermes: A Multi-Scale Spatial-Temporal Hypergraph Network for Stock Time Series Forecasting
110. NeurIPS 2026High-dimensional Gaussian Graphical Model Testing for Long-Memory Time Series
111. NeurIPS 2026History-Aware Conformal Prediction Sets for Censored Time-to-Event Outcomes
112. NeurIPS 2026Hitting a Moving Target: Test-Time Adaptation for AI Text Detection under Continual Distribution Shift
113. NeurIPS 2026Hitting Time Isomorphism for Multi-Stage Planning with Foundation Policies
114. NeurIPS 2026HyFAD: Hybrid Time-Frequency Diffusion with Frequency-Aware Embedding for Time Series Imputation
115. NeurIPS 2026Improving Audit Realism with Inference-Time Compute and Deployment Scaffolds
116. NeurIPS 2026IMTS-Tokenizer: Time-Aware Tokenization for Irregular Multivariate Time Series Forecasting
117. NeurIPS 2026InCLAD: A Continual Learning Benchmark for Industrial Visual Anomaly Detection
118. NeurIPS 2026Inference Time Nash Alignment
119. NeurIPS 2026Inference-time Alignment via Sparse Junction Steering
120. NeurIPS 2026Inference-Time Self-Aligned Drifting for Few-Step Flow Matching
121. NeurIPS 2026Internal Evaluation of Unsupervised Anomaly Detection Algorithms with Explanation
122. NeurIPS 2026Inverted Detection and Control in Steering Vectors
123. NeurIPS 2026JEDI: Real-Time Jailbreak Defense for LLMs via In-Generation Detection and Intervention
124. NeurIPS 2026Joint Consistency: A Unified Test-Time Aggregation Framework via Energy Minimization
125. NeurIPS 2026Kairos: Toward Adaptive and Parameter-Efficient Time Series Foundation Models
126. NeurIPS 2026Koopman Generative Operators for Efficient Probabilistic Time-Series Forecasting
127. NeurIPS 2026Layer Precision Reduction for Deep Anomaly Detection
128. NeurIPS 2026Learned Lagrangian Models of PDEs via Euler–Lagrange Residual Minimization
129. NeurIPS 2026Learning Collision‑Free Dispatch Policies for Route‑Wise Decision‑Dependent Anomaly Detection
130. NeurIPS 2026Learning Planning Budgets in Real-Time RL
131. NeurIPS 2026Learning to Trigger: Reinforcement Learning at the Large Hadron Collider
132. NeurIPS 2026Linear-time rule mining under formal guarantees
133. NeurIPS 2026Lipschitz Dueling Bandits over Continuous Action Spaces
134. NeurIPS 2026LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling
135. NeurIPS 2026LogSig-SSM: Time-Series Modelling with Multi-Scale Log-Signature Compression for State-Space Models
136. NeurIPS 2026Mamba Can Learn Low-Dimensional Targets In-Context via Test-Time Feature Learning
137. NeurIPS 2026Mamba Flow Matching Neural Processes: Linear-Time Inference for Irregularly Observed Spatial Fields
138. NeurIPS 2026Marrying Optimal Transport and ODEs for Unified Continuous-Time 4D Reconstruction and Tracking
139. NeurIPS 2026MDK-MoE: Multi-view Decomposed Kalman Mixture of Experts Framework for Non-stationary Time Series Forecasting
140. NeurIPS 2026Measure Less, Know More: Self-Supervised Test-Time Feature Acquisition
141. NeurIPS 2026Measuring Robustness and Efficiency in a Connectome-Constrained Fly Visual System Model on a Collision-Detection Task
142. NeurIPS 2026Membrane Sensitivity and Deployment Fragility of Learnable Time Constants in Spiking Neural Networks
143. NeurIPS 2026MissPath-FM: Flow Matching with Structured Priors for Partially Observed Time Series
144. NeurIPS 2026MMTA: Benchmarking Multimodal Temporal Analysis with Time Series, Text, and Vision
145. NeurIPS 2026Monotone Inclusion Approach to Weakly Monotone Discrete-Time Finite-Horizon Mean-Field Games
146. NeurIPS 2026MOSAIC: Module Discovery via Sparse Additive Identifiable Causal Learning for Scientific Time Series
147. NeurIPS 2026MSAR: Next-Scale Autoregressive Forecasting for Time Series via Modular Multi-Scale Decoupling
148. NeurIPS 2026Multivariate Time Series Forecasting needs Cross Variable Loss
149. NeurIPS 2026Near-Linear Time Generalized Sinkhorn Algorithms for Bounded Genus Graphs
150. NeurIPS 2026Near-Optimal Regret in Adversarial Kernel Bandits

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.