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

95 papers, page 2 of 2

51. ICLR 2024Multi-Resolution Diffusion Models for Time Series Forecasting
52. ICLR 2024NECO: NEural Collapse Based Out-of-distribution detection
53. ICLR 2024On Diffusion Modeling for Anomaly Detection
54. ICLR 2024On the Generalization and Approximation Capacities of Neural Controlled Differential Equations
55. ICLR 2024Online GNN Evaluation Under Test-time Graph Distribution Shifts
56. ICLR 2024Parametric Augmentation for Time Series Contrastive Learning
57. ICLR 2024Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting
58. ICLR 2024Periodicity Decoupling Framework for Long-term Series Forecasting
59. ICLR 2024Polynormer: Polynomial-Expressive Graph Transformer in Linear Time
60. ICLR 2024PROGRAM: PROtotype GRAph Model based Pseudo-Label Learning for Test-Time Adaptation
61. ICLR 2024REBAR: Retrieval-Based Reconstruction for Time-series Contrastive Learning
62. ICLR 2024Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning
63. ICLR 2024Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators
64. ICLR 2024RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies
65. ICLR 2024Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancement
66. ICLR 2024Self-Supervised Contrastive Learning for Long-term Forecasting
67. ICLR 2024SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations
68. ICLR 2024SocioDojo: Building Lifelong Analytical Agents with Real-world Text and Time Series
69. ICLR 2024Soft Contrastive Learning for Time Series
70. ICLR 2024Stabilizing Backpropagation Through Time to Learn Complex Physics
71. ICLR 2024Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data
72. ICLR 2024STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction
73. ICLR 2024T-Rep: Representation Learning for Time Series using Time-Embeddings
74. ICLR 2024TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series
75. ICLR 2024TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting
76. ICLR 2024Test-time Adaptation against Multi-modal Reliability Bias
77. ICLR 2024Test-Time Training on Nearest Neighbors for Large Language Models
78. ICLR 2024TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series
79. ICLR 2024TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts
80. ICLR 2024The Update-Equivalence Framework for Decision-Time Planning
81. ICLR 2024Time Fairness in Online Knapsack Problems
82. ICLR 2024Time Travel in LLMs: Tracing Data Contamination in Large Language Models
83. ICLR 2024Time-Efficient Reinforcement Learning with Stochastic Stateful Policies
84. ICLR 2024Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
85. ICLR 2024Time-Varying Propensity Score to Bridge the Gap between the Past and Present
86. ICLR 2024TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting
87. ICLR 2024Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach
88. ICLR 2024Towards Robust Offline Reinforcement Learning under Diverse Data Corruption
89. ICLR 2024Towards Transparent Time Series Forecasting
90. ICLR 2024Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting
91. ICLR 2024Transformer-VQ: Linear-Time Transformers via Vector Quantization
92. ICLR 2024Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation
93. ICLR 2024VQ-TR: Vector Quantized Attention for Time Series Forecasting
94. ICLR 2024Weakly Supervised Virus Capsid Detection with Image-Level Annotations in Electron Microscopy Images
95. ICLR 2024Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML

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.