Abstract: Predicting information popularity in social networks has become a central focus of network analysis. While recent advancements have been made, most existing approaches rely solely on the ...
This repository accompanies the first report on integrating variational autoencoders with normalizing flows into a comprehensive molecular design workflow. Our approach has generated novel molecules ...
ABSTRACT: Video-based anomaly detection in urban surveillance faces a fundamental challenge: scale-projective ambiguity. This occurs when objects of different physical sizes appear identical in camera ...
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Merck & Co. has doubled down on its partnership with Variational AI, striking a deal worth up to $349 million to collaborate on small molecule candidates against two targets. Variational disclosed a ...
Imagine this: you’re in the middle of an important project, juggling deadlines, and collaborating with a team scattered across time zones. Suddenly, your computer crashes, and hours of work vanish in ...
ABSTRACT: Anomaly detection in complex crowd scenes is a challenging task due to the inherent variability in crowd behaviors, interactions, and scales. This paper proposes a novel hybrid model that ...
Generative Modeling is a branch of machine learning that focuses on creating models representing distributions of data, denoted as $P(X)$. $X$ represents the data ...
A new technical paper titled “Generative AI for Analog Integrated Circuit Design: Methodologies and Applications” was published by researchers at McMaster University. “Electronic Design Automation ...
Antonia Haynes is a Game Rant writer who resides in a small seaside town in England where she has lived her whole life. Beginning her video game writing career in 2014, and having an avid love of ...
Abstract: Vector quantized variational autoencoders, as variants of variational autoencoders, effectively capture discrete representations by quantizing continuous latent spaces and are widely used in ...
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