在当前的AIGC浪潮中，扩散模型无疑是图像生成领域的绝对主力。我们熟知的 Stable Diffusion 等模型，大多在一种被称为“潜在空间”的低维数据空间里工作。这个潜在空间通常由一个变分自编码器（Variational Autoencoder, VAE）构建，其核心任务是尽可能无损地压缩和重建图像的像素细节。 与此同时，在计算机视觉的另一重要分支——视觉“理解”领域，像 DINO、CLIP ...

Researchers develop an AI-based platform that integrates reaction data with catalyst performance for the design of new ...

Abstract: In recent years, hyperspectral unmixing (HU) has been a crucial preprocess in hyperspectral imagery analysis. Current learning-based methods of HU are built on the autoencoder framework.

CatDRX is a generative AI framework developed at Institute of Science Tokyo, which enables the design of new chemical ...

Abstract: Forecasting traffic flow is an important task in urban areas, and a large number of methods have been proposed for traffic flow prediction. However, most of the existing methods follow a ...

Research shows AI models exhibit loss chasing, illusion of control, and risky behavior when given freedom in gambling ...

据AIbase报道，Meta AI研究团队近日发布了一项关于名为Pixio的图像模型的研究，表明即使采用更简单的训练路径，该模型在深度估计和3D重建等复杂视觉任务中也能表现出卓越的性能。长期以来，学术界普遍认为掩码自编码器（Masked Autoencoder, MAE）技术在场景理解方面不如DINOv2或DINOv3等更复杂的算法，但Pixio的出现打破了这一传统观念。

CatDRX is a generative AI framework developed at Institute of Science Tokyo, which enables the design of new chemical catalysts based on the specific chemical reactions in which they are used. The ...

CatDRX is a generative AI framework developed at Institute of Science Tokyo, which enables the design of new chemical catalysts based on the specific chemical reactions in which they are used. The ...

This toolbox enables the simple implementation of different deep autoencoder. The primary focus is on multi-channel time-series analysis. Each autoencoder consists of two, possibly deep, neural ...