Our system did one thing, and it did it well: It turned natural-language questions into API calls. The users were analysts, account managers, and operations leads. They knew what data they needed, but ...

Update: Tigramite now has a new CausalEffects class that allows to estimate (conditional) causal effects and mediation based on assuming a causal graph. Have a look at the tutorial. Further, Tigramite ...

Learn how to evaluate LLM quality and limitations using a range of testing techniques, from unit and regression testing to ...

Karpathy CLAUDE.md ten rules: a document attributed to Andrej Karpathy began circulating Friday, adding six agent self-check ...

AI benchmark cheating has been theorized as an inevitable consequence of training capable optimizers against fixed metrics. With OpenAI's GPT-5.6 Sol, the theory arrived in full view. The nonprofit ...

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.

Autoresearch for weather dycores. Contribute to khzhao/dynamaxx development by creating an account on GitHub.

Root Mean Square Error,Convolutional Neural Network,Feature Maps,Robotic System,Image Segmentation,Segmentation Accuracy,Adaptive Control,Attention Mechanism,Global Features,Local Features,Long ...

Root Mean Square Error,Long Short-term Memory,Neural Network,Attention Mechanism,Model Predictive Control,Recurrent Neural Network,Control Input,Convolutional Neural Network,Deep Learning,Model ...

So, this project wants to answer: Why does sparse regression often work well in practice, even when the usual theoretical assumptions do not clearly apply? We will study this question using ideas from ...