AI engineer Kyle Hessling merged two of Jackrong's Claude Opus 4.6 and GLM-5.1 distilled finetunes into a single ...

Abstract: Neural networks that overlook the underlying causal relationships among observed variables pose significant risks in high-stakes decision-making contexts due to concerns about the robustness ...

A decision tree regression system incorporates a set of if-then rules to predict a single numeric value. Decision tree regression is rarely used by itself because it overfits the training data, and so ...

Eric Gutiérrez, 6th February 2026. A Python implementation of a 1-hidden layer neural network built entirely from first principles. This project avoids deep learning libraries (like TensorFlow or ...

Kernel ridge regression (KRR) is a regression technique for predicting a single numeric value and can deliver high accuracy for complex, non-linear data. KRR combines a kernel function (most commonly ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...

Abstract: With the continuous expansion of automation and unmanned demand in industry, hydraulic cylinders, as one of the most important industrial actuators, urgently need fault diagnosis solutions ...

In recent years, something unexpected has been happening in artificial intelligence. Modern AI appears to be breaking a rule that statisticians have preached for nearly a century: Keep models in a ...

This repository provides implementation for SNBO (Scalable Neural Network-based Blackbox Optimization) — a novel method for efficient blackbox optimization using neural networks. It also includes code ...