- [R] TimeGPT : The first Generative Pretrained Transformer for Time-Series Forecasting https://aihorizonforecast.substack.com/p/timegpt-the-first-foundation-model 31 comments statistics
- [R] TimeGPT : The first Generative Pretrained Transformer for Time-Series Forecasting https://aihorizonforecast.substack.com/p/timegpt-the-first-foundation-model 46 comments machinelearning
Linking pages
- MOIRAI: Salesforce's Foundation Transformer For Time-Series Forecasting https://aihorizonforecast.substack.com/p/moirai-salesforces-foundation-transformer 49 comments
- AutoGluon-TimeSeries : Creating Powerful Ensemble Forecasts - Complete Tutorial https://aihorizonforecast.substack.com/p/autogluon-timeseries-creating-powerful 36 comments
- TimesFM: Google's Foundation Model For Time-Series Forecasting https://aihorizonforecast.substack.com/p/timesfm-googles-foundation-model 25 comments
- MOMENT: A Foundation Model for Time Series Forecasting, Classification, Anomaly Detection and Imputation https://aihorizonforecast.substack.com/p/moment-a-foundation-model-for-time 25 comments
- Tiny Time Mixers(TTMs): Powerful Zero/Few-Shot Forecasting Models by IBM https://aihorizonforecast.substack.com/p/tiny-time-mixersttms-powerful-zerofew?post_page-reds--= 18 comments
- GitHub - Nixtla/nixtla: TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀. https://github.com/Nixtla/nixtla 15 comments
- Tiny Time Mixers(TTMs): Powerful Zero/Few-Shot Forecasting Models by IBM https://aihorizonforecast.substack.com/p/tiny-time-mixersttms-powerful-zerofew?post_page-reml--= 15 comments
- TIME-MOE: Billion-Scale Time Series Foundation Model with Mixture-of-Experts https://aihorizonforecast.substack.com/p/time-moe-billion-scale-time-series 6 comments
- Tiny Time Mixers(TTMs): Powerful Zero/Few-Shot Forecasting Models by IBM https://aihorizonforecast.substack.com/p/tiny-time-mixersttms-powerful-zerofew?post_page-redlear--= 3 comments
Linked pages
- Time-Series Forecasting: Deep Learning vs Statistics — Who Wins? | by Nikos Kafritsas | Apr, 2023 | Towards Data Science https://medium.com/towards-data-science/time-series-forecasting-deep-learning-vs-statistics-who-wins-c568389d02df 85 comments
- https://arxiv.org/pdf/2101.02118.pdf 42 comments
- [2205.13504] Are Transformers Effective for Time Series Forecasting? https://arxiv.org/abs/2205.13504 7 comments
- [2001.08361] Scaling Laws for Neural Language Models https://arxiv.org/abs/2001.08361 0 comments
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