Beyond the lakehouse: Fundamental's NEXUS bypasses manual ETL with a native foundation model for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a simple sequence of words, but as a complex web of non-linear relationships.
IEEE

Wavelet-Enhanced Hybrid LSTM-XGBoost Model for Predicting Time Series Containing Unpredictable Events

Abstract: Accurate electricity consumption forecasting is essential for effective power management, especially in the presence of unpredictable events that disrupt typical consumption patterns. Using ...

Fundamental emerges from stealth with first major foundation model trained for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...
FinanceFeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
IEEE

ChronoTab: Forecasting Multivariate Time Series with Tabular LLMs

Abstract: Forecasting future values in multivariate time series is a critical challenge in many application domains, such as agriculture, transportation, energy, etc. Recently, Large Language Models ...