Time Series papers, 2023–2026
Forecasting and anomaly detection
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 2,157 papers are tagged with this topic.
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.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 91 | 60 | 62 | 59 | 272 |
| 2024 | 147 | 95 | 114 | 68 | 424 |
| 2025 | 221 | 131 | 159 | 74 | 585 |
| 2026 | 298 | 220 | 264 | 94 | 876 |
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 33 of 44
- ICLR 2024T-Rep: Representation Learning for Time Series using Time-Embeddings
- ICLR 2024TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series
- ICLR 2024TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting
- ICLR 2024Test-time Adaptation against Multi-modal Reliability Bias
- ICLR 2024Test-Time Training on Nearest Neighbors for Large Language Models
- ICLR 2024TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series
- ICLR 2024TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts
- ICLR 2024The Update-Equivalence Framework for Decision-Time Planning
- ICLR 2024Time Fairness in Online Knapsack Problems
- ICLR 2024Time Travel in LLMs: Tracing Data Contamination in Large Language Models
- ICLR 2024Time-Efficient Reinforcement Learning with Stochastic Stateful Policies
- ICLR 2024Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
- ICLR 2024Time-Varying Propensity Score to Bridge the Gap between the Past and Present
- ICLR 2024TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting
- ICLR 2024Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach
- ICLR 2024Towards Robust Offline Reinforcement Learning under Diverse Data Corruption
- ICLR 2024Towards Transparent Time Series Forecasting
- ICLR 2024Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting
- ICLR 2024Transformer-VQ: Linear-Time Transformers via Vector Quantization
- ICLR 2024Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation
- ICLR 2024VQ-TR: Vector Quantized Attention for Time Series Forecasting
- ICLR 2024Weakly Supervised Virus Capsid Detection with Image-Level Annotations in Electron Microscopy Images
- ICLR 2024Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML
- ICML 2024$S^2$IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
- ICML 2024A decoder-only foundation model for time-series forecasting
- ICML 2024A Dual-module Framework for Counterfactual Estimation over Time
- ICML 2024A Language Model’s Guide Through Latent Space
- ICML 2024A Linear Time and Space Local Point Cloud Geometry Encoder via Vectorized Kernel Mixture (VecKM)
- ICML 2024A Near-Linear Time Approximation Algorithm for Beyond-Worst-Case Graph Clustering
- ICML 2024A Subquadratic Time Algorithm for Robust Sparse Mean Estimation
- ICML 2024ALERT-Transformer: Bridging Asynchronous and Synchronous Machine Learning for Real-Time Event-based Spatio-Temporal Data
- ICML 2024An Analysis of Linear Time Series Forecasting Models
- ICML 2024An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series
- ICML 2024An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks
- ICML 2024An Unsupervised Approach for Periodic Source Detection in Time Series
- ICML 2024Arrows of Time for Large Language Models
- ICML 2024BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition
- ICML 2024Benign Overfitting in Adversarial Training of Neural Networks
- ICML 2024Beyond Individual Input for Deep Anomaly Detection on Tabular Data
- ICML 2024Bridging discrete and continuous state spaces: Exploring the Ehrenfest process in time-continuous diffusion models
- ICML 2024CATS: Enhancing Multivariate Time Series Forecasting by Constructing Auxiliary Time Series as Exogenous Variables
- ICML 2024CauDiTS: Causal Disentangled Domain Adaptation of Multivariate Time Series
- ICML 2024CLIPZyme: Reaction-Conditioned Virtual Screening of Enzymes
- ICML 2024Conformal prediction for multi-dimensional time series by ellipsoidal sets
- ICML 2024Conformalized Adaptive Forecasting of Heterogeneous Trajectories
- ICML 2024Consistent Adversarially Robust Linear Classification: Non-Parametric Setting
- ICML 2024Contamination-Resilient Anomaly Detection via Adversarial Learning on Partially-Observed Normal and Anomalous Data
- ICML 2024Convex Relaxations of ReLU Neural Networks Approximate Global Optima in Polynomial Time
- ICML 2024Decoding-time Realignment of Language Models
- ICML 2024Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization
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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.