Karpathy's 'autoresearch' agent did not improve its own code, but it points towards systems that could as well as towards way ...

Abstract: This article investigates the problem of partial node-based (PNB) recursive state estimation for complex networks (CNs) with unknown nonlinearities and energy harvesting sensors. To mitigate ...

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 ...

The Heisenberg uncertainty principle puts a limit on how precisely we can measure certain properties of quantum objects. But researchers may have found a way to bypass this limitation using a quantum ...

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 ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

This project explores the application of recursive neural networks (RNNs) in natural language processing, specifically for part-of-speech (POS) tagging. Drawing on foundational work by Socher et al.

Good morning. Welcome to the Jefferies London Healthcare Conference. My name is Dennis Ding, biotech analyst here at Jefferies. I have the wonderful pleasure of having Recursion Pharmaceuticals up ...

In modern broadband communication systems, radio frequency power amplifiers suffer from severe nonlinear distortion and memory effects. To accurately analyze the impact of their characteristics on ...