HydroGraphNet boosts watershed predictions of daily flow and nitrogen in sparse data regions

Spatially distributed prediction of streamflow and nitrogen (N) export dynamics is essential for precision management of ...
InfoQ

OpenAI Introduces Sparse Transformers for Deep Learning of Longer Sequences

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Business Wire

Numenta Demonstrates 100x Performance Acceleration in Deep Learning Networks Using Sparse Techniques

REDWOOD CITY, Calif.--(BUSINESS WIRE)--Numenta, Inc. announced it has achieved greater than 100x performance improvements on inference tasks in deep learning networks without any loss in accuracy. In ...
EurekAlert!

DSD-MatchingNet: Deformable sparse-to-dense feature matching for learning accurate correspondences

Detection methods based on deep convolutional networks search for interest points by constructing response maps using supervised, self-supervised, and unsupervised methods. Supervised methods use ...
VentureBeat

DeepMind makes big jump toward interpreting LLMs with sparse autoencoders

Large language models (LLMs) have made remarkable progress in recent years. But understanding how they work remains a challenge and scientists at artificial intelligence labs are trying to peer into ...
Geeky Gadgets

Giving AI memories with Sparse Priming Representation (SPR)

If you’ve ever marveled at the human brain’s remarkable ability to store and recall information, you’ll be pleased to know that researchers are hard at work trying to imbue artificial intelligence ...
Quanta Magazine

Sparse Networks Come to the Aid of Big Physics

Suppose you have a thousand-page book, but each page has only a single line of text. You’re supposed to extract the information contained in the book using a scanner, only this particular scanner ...