A New Way To See Life’s Hidden Chemistry: $10 Spectrometer Could Turn Wearables Into Personal Health Labs

Researchers have developed a compact, low-cost convolutional spectrometer that delivers lab-grade precision for applications ...
GitHub

3D U-Net Convolution Neural Network

We designed 3DUnetCNN to make it easy to apply and control the training and application of various deep learning models to medical imaging data. The links above give examples/tutorials for how to use ...
IEEE

Closed-Form Least-Squares Design of Fast-Convolution Based Variable-Bandwidth FIR Filters

Abstract: This paper introduces a closed-form least-squares (LS) design approach for fast-convolution (FC) based variable-bandwidth (VBW) finite-impulse-response (FIR) filters. The proposed LS design ...
PNAS

Convolution identities for divisor sums and modular forms

Our research proves a conjecture from string theory asserting the vanishing of a specific convolution sum arising in the 4-graviton scattering amplitude in 10-dimensional type IIB string theory. The ...
GitHub

Submanifold Sparse Convolutional Networks

This library brings Spatially-sparse convolutional networks to PyTorch. Moreover, it introduces Submanifold Sparse Convolutions, that can be used to build computationally efficient sparse ...
the-decoder

AI-generated CUDA kernels outperform PyTorch in several GPU-heavy machine learning benchmarks

A team at Stanford has shown that large language models can automatically generate highly efficient GPU kernels, sometimes outperforming the standard functions found in the popular machine learning ...
C&EN

Machine Learning Prediction of Optical Properties of Coumarin Derivatives Using Gaussian-Weighted Graph Convolution and Subgraph Modular Input

Department of Chemistry and Research Institute for Natural Science, Korea University, Seoul 02841, Korea ...