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Found 5 papers, 1 papers with code
Gradient Scaling on Deep Spiking Neural Networks with Spike-Dependent Local Information
Deep spiking neural networks (SNNs) are promising neural networks for their model capacity from deep neural network architecture and energy efficiency from SNNs' operations.
Mass Spectra Prediction with Structural Motif-based Graph Neural Networks
Mass spectra, which are agglomerations of ionized fragments from targeted molecules, play a crucial role across various fields for the identification of molecular structures.
E2V-SDE: From Asynchronous Events to Fast and Continuous Video Reconstruction via Neural Stochastic Differential Equations
In terms of image quality, the LPIPS score improves by up to 12% and the reconstruction speed is 87% higher than that of ET-Net.
GeoT: A Geometry-aware Transformer for Reliable Molecular Property Prediction and Chemically Interpretable Representation Learning
In recent years, molecular representation learning has emerged as a key area of focus in various chemical tasks.
Flexible dual-branched message passing neural network for quantum mechanical property prediction with molecular conformation
Message passing neural network provides an effective framework for capturing molecular geometric features with the perspective of a molecule as a graph.
