Feb. 8, 2024, 11:14 p.m. | Nikhil

MarkTechPost www.marktechpost.com

With the world of computational science continually evolving, physics-informed neural networks (PINNs) stand out as a groundbreaking approach for tackling forward and inverse problems governed by partial differential equations (PDEs). These models incorporate physical laws into the learning process, promising a significant leap in predictive accuracy and robustness.  But as PINNs grow in depth and […]

The post This AI Paper Introduces PirateNets: A Novel AI System Designed to Facilitate Stable and Efficient Training of Deep Physics-Informed Neural Network Models …

ai paper ai shorts ai system applications artificial intelligence computational deep learning differential editors pick groundbreaking laws machine learning network networks neural network neural networks novel novel ai paper physics physics-informed science staff tech news technology training world

More from www.marktechpost.com / MarkTechPost

Research Scholar (Technical Research)

@ Centre for the Governance of AI | Hybrid; Oxford, UK

HPC Engineer (x/f/m) - DACH

@ Meshcapade GmbH | Remote, Germany

Data Engineering Director-Big Data technologies (Hadoop, Spark, Hive, Kafka)

@ Visa | Bengaluru, India

Senior Data Engineer

@ Manulife | Makati City, Manulife Philippines Head Office

GDS Consulting Senior Data Scientist 2

@ EY | Taguig, PH, 1634

IT Data Analyst Team Lead

@ Rosecrance | Rockford, Illinois, United States