XElemNet: A Machine Learning Framework Applying Explainable AI (XAI) Suite for Deep Neural Networks in Materials Science
Deep learning has made progress in several fields and has also made its way into materials sciences. From tasks like ...
Tag: deep
The role of AI in motivation and deep learning
Key points: In the rapidly evolving ai landscape, education is at the forefront. New artificial intelligence tools for educators and ...
Deep learning vs data science: who will win? | by Benjamin Bodner | October 2024
What is more important, your data or your model?Source: author's imageThe two opponents enter the ring, each claiming to have ...
What happens when a state offers deep discounts on child care?
Teigue Linch remembers the email she received from Pine Forest, her daughters' child care center in Burlington, Vermont, encouraging families ...
TREAT: A deep learning framework that achieves high-precision modeling for a wide range of dynamical systems by injecting time-reversal symmetry as inductive bias
Dynamical systems are mathematical models that explain how a system evolves due to physical interactions or forces. These systems are ...
Dive deep into vector data stores using Amazon Bedrock Knowledge Bases
Customers across all industries are experimenting with generative ai to accelerate and improve business outcomes. Generative ai is used in ...
Understanding Automatic Differentiation in JAX: A Deep Dive | by Aamir Mushir Khan | October 2024
Releasing the Gradient: How JAX Makes Automatic Differentiation Look Like MagicW.Welcome to the world of JAX, where differentiation happens automatically, ...
Revisiting Weight Drop: Beyond Regularization in Modern Deep Learning
Weight decay and ℓ2 regularization are crucial in machine learning, especially to limit network capacity and reduce irrelevant weight components. ...
Exploring the connectivity of spatial input modes: Perspectives on adversarial detection and interpretation of deep neural networks
Input space modal connectivity in deep neural networks is based on research on excessive input invariance, blind spots, and connectivity ...
Microsoft releases GRIN MoE: a combination of gradient-based expert MoE models for efficient and scalable deep learning
artificial intelligence (ai) research has increasingly focused on improving the efficiency and scalability of deep learning models. These models have ...
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