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Lag-Llama: Open-Source Foundation Model for Time Series Forecasting
Towards Data Science
In October 2023, I published an article on TimeGPT, one of the first foundation model for time series forecasting, capable of zero-shot...
5 months ago
Nixtla Releases StatsForecast 1.7.5: Elevating Time Series Forecasting with MFLES and Scikit-Learn Integration
MarkTechPost
Nixtla unveiled StatsForecast 1.7.5, a significant update bringing new features and enhancements that further solidify its position as a...
1 month ago
Bayesian learning for the robust verification of autonomous robots | Communications Engineering
Nature
Autonomous robots used in infrastructure inspection, space exploration and other critical missions operate in highly dynamic environments.
6 months ago
AAAI-24 Tutorial and Lab List
The Association for the Advancement of Artificial Intelligence
Sponsored by the Association for the Advancement of Artificial Intelligence February 20-21, 2024 | Vancouver Convention Centre – West Building | Vancouver,...
8 months ago
TiDE: the ‘embarrassingly’ simple MLP that beats Transformers
Towards Data Science
As industries continue to evolve, the importance of an accurate forecasting becomes a non-negotiable asset whether you work in e-commerce, healthcare,...
7 months ago
Forecasting at Uber: An Introduction
Uber
This article is the first in a series dedicated to explaining how Uber leverages forecasting to build better products and services.
70 months ago
Exploring MSR Asia’s contributions to ICLR 2023: From robust machine learning to responsible AI
Microsoft
ICLR is recognized as one of the most influential international academic conferences in machine learning. At this year's conference,...
14 months ago
4. Supervised Learning: Models and Concepts - Machine Learning and Data Science Blueprints for Finance [Book]
O'Reilly Media
Chapter 4. Supervised Learning: Models and Concepts Supervised learning is an area of machine learning where the chosen algorithm tries to fit a target...
40 months ago
Robust seismicity forecasting based on Bayesian parameter estimation for epidemiological spatio-temporal aftershock clustering models
Nature
In the immediate aftermath of a strong earthquake and in the presence of an ongoing aftershock sequence, scientific advisories in terms of...
83 months ago
Temporal Fusion Transformer: A Primer on Deep Forecasting in Python
Towards Data Science
End-to-End Example: Probabilistic Time Series Forecasts Using the TFT, an Attention-Based Neural Network. Heiko Onnen. Towards Data Science.
31 months ago