VANCOUVER, British Columbia--(BUSINESS WIRE)--Variational AI, the company behind Enki™, an advanced foundation model for small molecule drug discovery, today ...
Replace the VAE algorithm in the paper《Design of diverse, functional mitochondrial targeting sequences across eukaryotic organisms using variational autoencoder》with the QBM-VAE algorithm, ...
ABSTRACT: Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management. Conventional asset pricing models, such as the Fama-French three-factor ...
Abstract: Variational Autoencoder(VAE) combines the ideas of autoencoders and variational inference, introducing the concept of latent space and variational inference to endow autoencoders to generate ...
Generating the periodic structure of stable materials is a long-standing challenge for the material design community. This task is difficult because stable materials only exist in a low-dimensional ...
This is a variational autoencoder based baseline for the DCASE2025 Challenge Task 2 (DCASE2025T2), the DCASE2024 Challenge Task 2 (DCASE2024T2) and the DCASE2023 Challenge Task 2 (DCASE2023T2). This ...
Abstract: The variational autoencoder (VAE) has proven highly effective in monitoring nonlinear stochastic processes, primarily under the assumption of complete and temporally independent data.
ABSTRACT: Predicting molecular properties is essential for advancing for advancing drug discovery and design. Recently, Graph Neural Networks (GNNs) have gained prominence due to their ability to ...
On Monday, U.S. markets were shaken by DeepSeek, a relatively new Chinese AI firm that poses a significant threat to its American competitors. After the company revealed its model, which answers ...
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