Understanding the role of linear ubiquitination in T-tubule biogenesis

Transverse tubules (T-tubules) play a significant role in muscle contraction. However, the underlying mechanism of their ...
TMCnet

MicroCloud Hologram Inc. Releases Learnable Quantum Spectral Filter Technology for Hybrid Graph Neural Networks

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released learnable quantum spectral filter technology for hybrid graph neural networks. This ...
GitHub

[convolution] Intermediate matrix rather than list for

Convolution seems like a good target example for #270, since we’ll need a way to specify/navigate to the appropriate intermediate value for the weightedSum computation. Currently weightedSum is ...
The New York Times

Here’s Why ‘The Matrix’ Is More Relevant Than Ever

One scene reflects the themes — A.I., fake news, transgender lives and Gen X — that make the film a classic. By Alissa Wilkinson Neo, the hero of “The Matrix,” is sure he lives in 1999. He has a green ...
GitHub

Alternative implementation of Multi-Head Mamba

First, congratulations on release of Mamba 2.0. I wanted to let you know that I have published a fork of Mamba 1.0 that much like Mamba 2.0 happens to add support for multi-head SSMs, associated block ...
marktechpost

Capsule Networks: Addressing Limitations of Convolutional Neural Networks CNNs

Convolutional Neural Networks (CNNs) have become the benchmark for computer vision tasks. However, they have several limitations, such as not effectively capturing spatial hierarchies and requiring ...
Ars Technica

Matrix multiplication advancement could lead to faster, more efficient AI models

Computer scientists have discovered a new way to multiply large matrices faster than ever before by eliminating a previously unknown inefficiency, reports Quanta Magazine. This could eventually ...
IEEE

Transfer Learning With Singular Value Decomposition of Multichannel Convolution Matrices

Abstract: The task of transfer learning using pretrained convolutional neural networks is considered. We propose a convolution-SVD layer to analyze the convolution operators with a singular value ...