Many enterprise RAG pipelines handle one type of search well and fail silently on the rest. Databricks on March 4 released a new agent called KARL, or Knowledge Agents via Reinforcement Learning, that ...

Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.

Visualize free body diagrams using vector math in Python to better understand forces and motion. This video shows how vectors represent forces, how they combine mathematically, and how Python helps ...

Abstract: Anomaly detection in multivariate time series (MTS) is crucial in domains such as industrial monitoring, cybersecurity, healthcare, and autonomous driving. Deep learning approaches have ...

Matt Katz (left) and Jake Welty (right) reveal the one-of-one Vector M12 racecar. Video by Drew Manley (Cooled Collective) In a nondescript storage facility on the outskirts of Los Angeles, a small ...

├── src/ # Source code │ ├── data_utils.py # Data generation and loading utilities │ ├── models.py # Time series forecasting models │ ├── visualization.py # Visualization utilities │ ├── main.py # ...

Bootstrap procedures for local projections typically rely on assuming that the data generating process (DGP) is a finite order vector autoregression (VAR), often taken to be that implied by the local ...

ABSTRACT: This study develops and empirically calibrates the Community-Social Licence-Insurance Equilibrium (CoSLIE) Model, a dynamic, multi-theoretic framework that reconceptualises ...

This paper proposes a “quasi-agnostic” sign restriction procedure to identify structural shocks in frequentist structural vector autoregression (SVAR) models. It argues that low acceptance rates, ...

Abstract: The article considers the problem of forecasting the volume of seasonal logistics transportation of fruits and vegetables using time series based on the seasonal autoregressive integrated ...