{"product_id":"advanced-analytics-and-learning-on-temporal-data-ebook","title":"Advanced Analytics and Learning on Temporal Data","description":"\u003cp\u003ee-SMOTE: a train set rebalancing algorithm for time series classification.- The Next Motif: Tapping into Recurrence Dynamics and Precursor Signals to Forecast Events of Interest.- Re-framing Time Series Augmentation Through the Lens of Generative Models.- FuelCast: Benchmarking Tabular and Temporal Models for Ship Fuel Consumption.- MoTM: Towards a Foundation Model for Time Series Imputation based on Continuous Modeling.- A Deep Dive into Alternatives to the Global Average Pooling for Time Series Classification.- Adaptive Fine-Tuning via Pattern Specialization for Deep Time Series Forecasting.- Unsupervised Feature Construction for Time Series Anomaly Detection - An Evaluation.- Multi-output Ensembles for Multi-step Forecasting.- Time series extrinsic regression algorithms for forecasting long time series with a short horizon.- Towards a Library for the Analysis of Temporal Sequences.- FiTEM: Fine-tuning Time-series Foundation Models for Selective Forecasting.- T3A-LLM: A Two-Stage Temporal Knowledge Graph Alignment Method Enhanced by LLM.\u003c\/p\u003e","brand":"Vincent Lemaire","offers":[{"title":"Default Title","offer_id":53628290662727,"sku":"9783032155351","price":53.49,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0920\/5455\/2903\/files\/advanced-analytics-and-learning-on-temporal-data-ebook.webp?v=1775025438","url":"https:\/\/www.cinebuch.de\/products\/advanced-analytics-and-learning-on-temporal-data-ebook","provider":"CineBuch","version":"1.0","type":"link"}