Time Series Analysis

FreqMoE: Enhancing Time Series Forecasting through Frequency Decomposition Mixture of Experts AISTATS 2025 Frequency-Masked Embedding Inference: A Non-Contrastive Approach for Time Series Representation Learning AAAI 2025 GCAD: Anomaly Detection in Multivariate Time Series from the Perspective of Granger Causality AAAI 2025 GCF: Estimating Unobserved Demand Using Graph Causal Forecasting AAAI 2025 Generalization bounds for mixing processes via delayed online-to-PAC conversions ALT 2025 Generating Hypotheses of Dynamic Causal Graphs in Neuroscience: Leveraging Generative Factor Models of Observed Time Series ICML 2025 GIST: Gear Type Identification by Spatiotemporal Trajectory Transformation for Monitoring Fisheries AAAI 2025 Graph Mixture of Experts and Memory-augmented Routers for Multivariate Time Series Anomaly Detection AAAI 2025 HAR-former: Hybrid Transformer with an Adaptive Time-Frequency Representation Matrix for Long-Term Series Forecasting AISTATS 2025 Harnessing Vision Models for Time Series Analysis: A Survey IJCAI 2025 HDT: Hierarchical Discrete Transformer for Multivariate Time Series Forecasting AAAI 2025 Hubness Change Point Detection AAAI 2025 Human-Machine Ritual: Synergic Performance through Real-Time Motion Recognition NeurIPS 2025 HyperMixer: Specializable Hypergraph Channel Mixing for Long-term Multivariate Time Series Forecasting AAAI 2025 Identifying Predictions That Influence the Future: Detecting Performative Concept Drift in Data Streams AAAI 2025 In-Context Fine-Tuning for Time-Series Foundation Models ICML 2025 KAN-AD: Time Series Anomaly Detection with Kolmogorov–Arnold Networks ICML 2025 KernelMatmul: Scaling Gaussian Processes to Large Time Series AAAI 2025 Latent Process Models for Functional Network Data JMLR 2025 Learning Soft Sparse Shapes for Efficient Time-Series Classification ICML 2025 Learning Time-Varying Multi-Region Brain Communications via Scalable Markovian Gaussian Processes ICML 2025 Learning to Extrapolate and Adjust: Two-Stage Meta-Learning for Concept Drift in Online Time Series Forecasting IJCAI 2025 Learning with Expected Signatures: Theory and Applications ICML 2025 LETS-C: Leveraging Text Embedding for Time Series Classification ACL 2025 LETS Forecast: Learning Embedology for Time Series Forecasting ICML 2025