TS-ICL: a Time-Indexed Foundation Model for Time Series Forecasting & Imputation via In-Context Learning
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Jun 30, 2026 - Python
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times-series
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Automated Bayesian model discovery for time series data
machine-learning forecasting bayesian-inference structure-learning icml gaussian-process times-series
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Jun 19, 2026 - Julia
AutoTCL and Parametric Augmentation for Time Series Contrastive Learning(ICLR2024)
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Mar 24, 2024 - Python
Linear-time sequence modeling that replaces attention's O(n²d) complexity with O(nd) summation-based aggregation. Demonstrates constraint-driven emergence: how functional representations can develop from optimization pressure and architectural constraints alone, without explicit pairwise interactions.
intelligence deep-learning embeddings transformer forecasting attention cybernetics representation representation-theory attention-mechanism self-organization learning-theory attention-is-all-you-need emergence multimodal linear-time times-series llm system-theory sequence-modelling
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Nov 3, 2025 - Python
Demand forecasting and rebalancing analysis of urban bikeshare systems across multiple cities, using riders' patterns to inform fleet distribution strategy.
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Mar 27, 2026 - Jupyter Notebook
🌦️ Deep Learning RNN Project: Predict Seattle's Weather with LSTM 🌡️
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Mar 6, 2025 - Python
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