Interpretability in deep learning for finance: A case study for the Heston model

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...
Ars Technica

How a stubborn computer scientist accidentally launched the deep learning boom

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...

Identifying potential drug candidates with deep learning virtual screening

The earliest stage of drug discovery is governed by a simple constraint: there are far more possible drug-like molecules than any pharmaceutical laboratory could ever test. A new deep learning system, ...
EurekAlert!

Transfer learning-enhanced physics-informed neural network (TLE-PINN): A breakthrough in melt pool prediction for laser melting

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...
The Scientist

Artificial Neural Networks: Learning by Doing

Article reviewed by Grace Lindsay, PhD from New York University. Scientists design ANNs to function like neurons. 6 They write lines of code in an algorithm such that there are nodes that each contain ...

Guide Labs debuts a new kind of interpretable LLM

The company open-sourced an 8 billion parameter LLM, Steerling-8B, trained with a new architecture designed to make its ...
Hosted on MSN

Deep Neural Network From Scratch in Python ¦ Fully Connected Feedforward Neural Network

Create a fully connected feedforward neural network from the ground up with Python — unlock the power of deep learning! New details in Charlie Kirk shooting as his widow breaks her silence Trump ...