Nowadays, artificial intelligence is present in almost every part of our lives. Smartphones, social media feeds, recommendation engines, online ad networks, and navigation tools are… Read More »Connections between Neural Networks and Pure Mathematics
Picture by By Tatiana Shepeleva/shutterstock.com One of the most challenging problems in modern theoretical physics is the so-called many-body problem. Typical many-body systems are composed… Read More »Neural Quantum States
The gradient descent algorithm is one of the most popular optimization techniques in machine learning. It comes in three flavors: batch or “vanilla” gradient descent (GD), stochastic gradient… Read More »Machine Learning and Particle Motion in Liquids: An Elegant Link
Introduction It is a well-known fact that neural networks can approximate the output of any continuous mathematical function, no matter how complicated it might be. Take… Read More »The Approximation Power of Neural Networks (with Python codes)
