neural networks
Artificial Intelligence
Optimizing Deep Learning Models with SAM
: Overparameterization, Generalizability, and SAM
The dramatic success of recent deep learning — especially within the domains of Computer Vision and Natural Language Processing — is built on “overparameterized” models: models with good enough parameters to memorize the training data...
Artificial Intelligence
On the Possibility of Small Networks for Physics-Informed Learning
Introduction
within the period of 2017-2019, physics-informed neural networks (PINNs) have been a very talked-about area of research within the scientific machine learning (SciML) community . PINNs are used to unravel atypical and partial...
Artificial Intelligence
How Convolutional Neural Networks Learn Musical Similarity
audio embeddings for music advice?
Streaming platforms (Spotify, Apple Music, etc.) must have the power to recommend recent songs to their users. The higher the recommendations, the higher the listening experience.
There are various ways...
Artificial Intelligence
Guided learning lets “untrainable” neural networks realize their potential
Even networks long considered “untrainable” can learn effectively with a little bit...
Artificial Intelligence
Deep-learning model predicts how fruit flies form, cell by cell
During early development, tissues and organs begin to bloom through the shifting,...
Artificial Intelligence
AI Papers to Read in 2025
with my series of AI paper recommendations. My long-term followers might recall the 4 previous editions (, , , and ). I’ve been away from writing for quite a while, and I couldn’t...
Artificial Intelligence
A faster problem-solving tool that guarantees feasibility
Managing an influence grid is like trying to unravel an infinite puzzle.Grid...
Artificial Intelligence
A brand new method to edit or generate images
AI image generation — which relies on neural networks to create latest...
Recent posts
