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

147 papers, page 3 of 3

101. NeurIPS 2024Rethinking Out-of-Distribution Detection on Imbalanced Data Distribution
102. NeurIPS 2024Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple Remedy
103. NeurIPS 2024Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion Perspective
104. NeurIPS 2024Rough Transformers: Lightweight and Continuous Time Series Modelling through Signature Patching
105. NeurIPS 2024Safe Time-Varying Optimization based on Gaussian Processes with Spatio-Temporal Kernel
106. NeurIPS 2024SARAD: Spatial Association-Aware Anomaly Detection and Diagnosis for Multivariate Time Series
107. NeurIPS 2024Scaling Law for Time Series Forecasting
108. NeurIPS 2024SDformer: Similarity-driven Discrete Transformer For Time Series Generation
109. NeurIPS 2024Segment, Shuffle, and Stitch: A Simple Layer for Improving Time-Series Representations
110. NeurIPS 2024Shape analysis for time series
111. NeurIPS 2024SMART: Towards Pre-trained Missing-Aware Model for Patient Health Status Prediction
112. NeurIPS 2024SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion
113. NeurIPS 2024SOI: Scaling Down Computational Complexity by Estimating Partial States of the Model
114. NeurIPS 2024SolarCube: An Integrative Benchmark Dataset Harnessing Satellite and In-situ Observations for Large-scale Solar Energy Forecasting
115. NeurIPS 2024Space-Time Continuous PDE Forecasting using Equivariant Neural Fields
116. NeurIPS 2024Structured Matrix Basis for Multivariate Time Series Forecasting with Interpretable Dynamics
117. NeurIPS 2024TALoS: Enhancing Semantic Scene Completion via Test-time Adaptation on the Line of Sight
118. NeurIPS 2024Task-oriented Time Series Imputation Evaluation via Generalized Representers
119. NeurIPS 2024Terra: A Multimodal Spatio-Temporal Dataset Spanning the Earth
120. NeurIPS 2024Test-time Adaptation in Non-stationary Environments via Adaptive Representation Alignment
121. NeurIPS 2024Test-Time Adaptation Induces Stronger Accuracy and Agreement-on-the-Line
122. NeurIPS 2024Test-Time Dynamic Image Fusion
123. NeurIPS 2024Testing Calibration in Nearly-Linear Time
124. NeurIPS 2024The Elephant in the Room: Towards A Reliable Time-Series Anomaly Detection Benchmark
125. NeurIPS 2024The Fine-Grained Complexity of Gradient Computation for Training Large Language Models
126. NeurIPS 2024Time Makes Space: Emergence of Place Fields in Networks Encoding Temporally Continuous Sensory Experiences
127. NeurIPS 2024Time-Constrained Robust MDPs
128. NeurIPS 2024Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting
129. NeurIPS 2024Time-MMD: Multi-Domain Multimodal Dataset for Time Series Analysis
130. NeurIPS 2024Time-Reversal Provides Unsupervised Feedback to LLMs
131. NeurIPS 2024TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables
132. NeurIPS 2024Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series
133. NeurIPS 2024TinyTTA: Efficient Test-time Adaptation via Early-exit Ensembles on Edge Devices
134. NeurIPS 2024Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms
135. NeurIPS 2024Towards Editing Time Series
136. NeurIPS 2024Towards Understanding Evolving Patterns in Sequential Data
137. NeurIPS 2024TPC: Test-time Procrustes Calibration for Diffusion-based Human Image Animation
138. NeurIPS 2024Trajectory Flow Matching with Applications to Clinical Time Series Modelling
139. NeurIPS 2024Tri-Level Navigator: LLM-Empowered Tri-Level Learning for Time Series OOD Generalization
140. NeurIPS 2024TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series
141. NeurIPS 2024UniMTS: Unified Pre-training for Motion Time Series
142. NeurIPS 2024UniTS: A Unified Multi-Task Time Series Model
143. NeurIPS 2024Using Time-Aware Graph Neural Networks to Predict Temporal Centralities in Dynamic Graphs
144. NeurIPS 2024Utilizing Image Transforms and Diffusion Models for Generative Modeling of Short and Long Time Series
145. NeurIPS 2024When are dynamical systems learned from time series data statistically accurate?
146. NeurIPS 2024When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL
147. NeurIPS 2024YOLOv10: Real-Time End-to-End Object Detection

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.