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

875 papers, page 15 of 18

701. NeurIPS 2026Joint Consistency: A Unified Test-Time Aggregation Framework via Energy Minimization
702. NeurIPS 2026Kairos: Toward Adaptive and Parameter-Efficient Time Series Foundation Models
703. NeurIPS 2026Koopman Generative Operators for Efficient Probabilistic Time-Series Forecasting
704. NeurIPS 2026Layer Precision Reduction for Deep Anomaly Detection
705. NeurIPS 2026Learned Lagrangian Models of PDEs via Euler–Lagrange Residual Minimization
706. NeurIPS 2026Learning Collision‑Free Dispatch Policies for Route‑Wise Decision‑Dependent Anomaly Detection
707. NeurIPS 2026Learning Planning Budgets in Real-Time RL
708. NeurIPS 2026Learning to Trigger: Reinforcement Learning at the Large Hadron Collider
709. NeurIPS 2026Linear-time rule mining under formal guarantees
710. NeurIPS 2026Lipschitz Dueling Bandits over Continuous Action Spaces
711. NeurIPS 2026LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling
712. NeurIPS 2026LogSig-SSM: Time-Series Modelling with Multi-Scale Log-Signature Compression for State-Space Models
713. NeurIPS 2026Mamba Can Learn Low-Dimensional Targets In-Context via Test-Time Feature Learning
714. NeurIPS 2026Mamba Flow Matching Neural Processes: Linear-Time Inference for Irregularly Observed Spatial Fields
715. NeurIPS 2026Marrying Optimal Transport and ODEs for Unified Continuous-Time 4D Reconstruction and Tracking
716. NeurIPS 2026MDK-MoE: Multi-view Decomposed Kalman Mixture of Experts Framework for Non-stationary Time Series Forecasting
717. NeurIPS 2026Measure Less, Know More: Self-Supervised Test-Time Feature Acquisition
718. NeurIPS 2026Measuring Robustness and Efficiency in a Connectome-Constrained Fly Visual System Model on a Collision-Detection Task
719. NeurIPS 2026Membrane Sensitivity and Deployment Fragility of Learnable Time Constants in Spiking Neural Networks
720. NeurIPS 2026MissPath-FM: Flow Matching with Structured Priors for Partially Observed Time Series
721. NeurIPS 2026MMTA: Benchmarking Multimodal Temporal Analysis with Time Series, Text, and Vision
722. NeurIPS 2026Monotone Inclusion Approach to Weakly Monotone Discrete-Time Finite-Horizon Mean-Field Games
723. NeurIPS 2026MOSAIC: Module Discovery via Sparse Additive Identifiable Causal Learning for Scientific Time Series
724. NeurIPS 2026MSAR: Next-Scale Autoregressive Forecasting for Time Series via Modular Multi-Scale Decoupling
725. NeurIPS 2026Multivariate Time Series Forecasting needs Cross Variable Loss
726. NeurIPS 2026Near-Linear Time Generalized Sinkhorn Algorithms for Bounded Genus Graphs
727. NeurIPS 2026Near-Optimal Regret in Adversarial Kernel Bandits
728. NeurIPS 2026Neural Continuous-Time Markov Chain: Discrete Diffusion via Decoupled Jump Timing and Direction
729. NeurIPS 2026Neural Fractional Stochastic Differential Equations
730. NeurIPS 2026Neural Neural Scaling Laws
731. NeurIPS 2026Neural Optimal Transport in Hilbert Spaces
732. NeurIPS 2026Neurosymbolic Learning for Inference-Time Argumentation
733. NeurIPS 2026NOCE-Net: Representation Learning for Battery Operational Context via Nested Sequence Modelling
734. NeurIPS 2026NPUsper: Eliminating Redundant Computation for Real-Time Whisper on Mobile NPUs
735. NeurIPS 2026OATS: Online Data Augmentation for Time Series Foundation Models
736. NeurIPS 2026Observable Neural ODEs for Identifiable Causal Forecasting in Continuous Time
737. NeurIPS 2026Observations Drift, Structures Remain: Structural Pretraining with Time Alignment for Electromagnetic Signals
738. NeurIPS 2026ODEWorld: A Continuous Predictive Architecture via Physical-Time Flow
739. NeurIPS 2026OHATP: Graph Anomaly Detection with Orthogonal-Hyperspherical Augmentation and Topology Perception
740. NeurIPS 2026On the Complexity of Discounted Robust MDPs with $L_p$ Uncertainty Sets
741. NeurIPS 2026On the Origin of Algorithmic Progress in AI: Evidence from Language Model Pre-Training
742. NeurIPS 2026One Language-Free Foundation Model Is Enough for Universal Vision Anomaly Detection
743. NeurIPS 2026One Loss to Rule Them All: Marked Time-to-Event for Structured EHR Foundation Models
744. NeurIPS 2026One More Time: Revisiting Neural Quantum States from a Reinforcement Learning Perspective
745. NeurIPS 2026One-Time Soft Alignment Enables Resilient Learning without Weight Transport
746. NeurIPS 2026Online Change-point Detection using Foundation Probabilistic Forecasting Models
747. NeurIPS 2026Optimal Contextual Pricing under Agnostic Non-Lipschitz Demand
748. NeurIPS 2026Ordinary Least Squares as an Attention Mechanism
749. NeurIPS 2026PAC-Bayesian Bounds for Learning Partially Observed Stochastic Linear Time-Invariant State-Space Systems with Inputs and Sub-Gaussian Noise
750. NeurIPS 2026PACEvolve++: Improving Test-time Learning for Evolutionary Search Agents

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.