O n Tuesday, researchers at Stanford and Yale revealed something that AI companies would prefer to keep hidden. Four popular ...
An AI model that learns without human input—by posing interesting queries for itself—might point the way to superintelligence ...
Tessellations aren’t just eye-catching patterns—they can be used to crack complex mathematical problems. By repeatedly ...
Beijing, Jan. 05, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning ...
Abstract: Classification of electroencephalogram-based motor imagery (MI-EEG) tasks is crucial in brain–computer interface (BCI). EEG signals require a large number of channels in the acquisition ...
Imagine Jo: Everyone in Jo's life recognizes her as an outstanding problem solver. She's the type of person who seems capable of almost anything. Jo excels at intuitive problem-solving. Over her life, ...
KernelOptimizer is an open-source tool that automates CUDA kernel optimization for PyTorch workloads using large language models (LLMs). Inspired by Stanford CRFM’s fast kernel research, it leverages ...
This repository contains the implementation of AdaptConv for point cloud analysis. Adaptive Graph Convolution (AdaptConv) is a point cloud convolution operator presented in our ICCV2021 paper. If you ...
Abstract: Convolution and self-attention are two powerful techniques for multisource remote sensing (RS) data fusion that have been widely adopted in Earth observation tasks. However, convolutional ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback