Abstract: We introduce a Conditional Variational Autoencoder (CVAE) surrogate for exoplanet spectral modeling, trained on a wide grid of synthetic spectra spanning key planetary regimes. By tuning ...

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 ...

You can use any of our models with torch.hub.load. We provide 2 classes of models for each of our 3 submodels of the CVAE-WGAN architecture cvae-wgan submodels: - CVAE: Conditional Variational ...

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 ...

Fine-grained, continuous control over multiple attributes at once (e.g., exact eye-openness and car width) on top of any pretrained diffusion model. A decoupled cross-attention layer that cleanly ...

Abstract: In this article, we propose a novel conditional generative flow-induced variational autoencoder (CGlow-VAE) model to address the critical challenge of the small sample issue in plasma ...

Researchers have long sought to bridge the gap between phenotypes and the genotypes that cause them. This gap remains open because current methods focus on associating phenotypes to a combinatorially ...

An illustration of a magnifying glass. An illustration of a magnifying glass.