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

272 papers, page 3 of 6

101. ICLR 2023Robust Multivariate Time-Series Forecasting: Adversarial Attacks and Defense Mechanisms
102. ICLR 2023Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting
103. ICLR 2023Score-based Continuous-time Discrete Diffusion Models
104. ICLR 2023Sequential Latent Variable Models for Few-Shot High-Dimensional Time-Series Forecasting
105. ICLR 2023Spatial Attention Kinetic Networks with E(n)-Equivariance
106. ICLR 2023SpeedyZero: Mastering Atari with Limited Data and Time
107. ICLR 2023Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation
108. ICLR 2023TEMPERA: Test-Time Prompt Editing via Reinforcement Learning
109. ICLR 2023Temporal Dependencies in Feature Importance for Time Series Prediction
110. ICLR 2023Test-Time Robust Personalization for Federated Learning
111. ICLR 2023TiAda: A Time-scale Adaptive Algorithm for Nonconvex Minimax Optimization
112. ICLR 2023Time to augment self-supervised visual representation learning
113. ICLR 2023Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detection
114. ICLR 2023TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis
115. ICLR 2023Towards Lightweight, Model-Agnostic and Diversity-Aware Active Anomaly Detection
116. ICLR 2023Towards Understanding GD with Hard and Conjugate Pseudo-labels for Test-Time Adaptation
117. ICLR 2023TrojText: Test-time Invisible Textual Trojan Insertion
118. ICLR 2023Uniform-in-time propagation of chaos for the mean-field gradient Langevin dynamics
119. ICLR 2023Unsupervised Model Selection for Time Series Anomaly Detection
120. ICML 2023A new near-linear time algorithm for k-nearest neighbor search using a compressed cover tree
121. ICML 2023Accounting For Informative Sampling When Learning to Forecast Treatment Outcomes Over Time
122. ICML 2023AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation
123. ICML 2023Adaptive Estimation of Graphical Models under Total Positivity
124. ICML 2023Adversarially Robust PAC Learnability of Real-Valued Functions
125. ICML 2023Bandits with Knapsacks: Advice on Time-Varying Demands
126. ICML 2023Bayesian online change point detection with Hilbert space approximate Student-t process
127. ICML 2023Conditional Tree Matching for Inference-Time Adaptation of Tree Prediction Models
128. ICML 2023Context Consistency Regularization for Label Sparsity in Time Series
129. ICML 2023Deep Anomaly Detection under Labeling Budget Constraints
130. ICML 2023Deep Latent State Space Models for Time-Series Generation
131. ICML 2023Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time
132. ICML 2023Delayed Bandits: When Do Intermediate Observations Help?
133. ICML 2023Delving into Noisy Label Detection with Clean Data
134. ICML 2023Detecting Out-of-distribution Data through In-distribution Class Prior
135. ICML 2023Diagnosis, Feedback, Adaptation: A Human-in-the-Loop Framework for Test-Time Policy Adaptation
136. ICML 2023Dissecting the Effects of SGD Noise in Distinct Regimes of Deep Learning
137. ICML 2023Divide and Conquer Dynamic Programming: An Almost Linear Time Change Point Detection Methodology in High Dimensions
138. ICML 2023Domain Adaptation for Time Series Under Feature and Label Shifts
139. ICML 2023Dynamic Constrained Submodular Optimization with Polylogarithmic Update Time
140. ICML 2023Estimating the Contamination Factor's Distribution in Unsupervised Anomaly Detection
141. ICML 2023Fascinating Supervisory Signals and Where to Find Them: Deep Anomaly Detection with Scale Learning
142. ICML 2023Fast Rates in Time-Varying Strongly Monotone Games
143. ICML 2023Feature Programming for Multivariate Time Series Prediction
144. ICML 2023Forget Unlearning: Towards True Data-Deletion in Machine Learning
145. ICML 2023Implicit Neural Spatial Representations for Time-dependent PDEs
146. ICML 2023Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks?
147. ICML 2023Learning Deep Time-index Models for Time Series Forecasting
148. ICML 2023Learning Perturbations to Explain Time Series Predictions
149. ICML 2023Leveraging Proxy of Training Data for Test-Time Adaptation
150. ICML 2023Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA

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.