Numerous AI model architectures have been developed for generative molecular design e.g. variational autoencoders (VAE) [14,15], generative adversarial networks(GAN) [16], recurrent neural networks (RNN) [6,17,18,19,20], transformers [21,22], flow models [23,24] and diffusion models [25...
education through AI-driven innovations. Section1of this paper provides an overview of the various forms and techniques of generative AI. Section2discusses the prospect of generative AI in orthopedic education. Section3assesses the current performance of AI in orthopedic examinations. Section4discusses t...
Two of the most prominent methods for producing AI-generated material are variational autoencoders (VAE) and generative adversarial networks (GAN). VAEs are autoencoders that specialize in dimensionality reduction and minimize the error between reconstructed data and original data. VAEs are highly ...
scTour is a new deep learning architecture that builds on the framework of variational autoencoder (VAE) [13] and neural ordinary differential equation (ODE) [14] accompanied by critical innovations tailored to the analysis of dynamic processes using single-cell genomic data (Fig.1). Specifically...
World Models consists of three main components: Vision (V), Model (M), and Controller (C) that interact together to form an agent:V consists of a convolutional Variational Autoencoder (VAE), which compresses frames taken from the gameplay into a latent vector z. M consists of a Mixture ...
which can usually be proxied in the form of mathematical models. Typically, they do not consider the underlying principles and physical mechanisms of the modeled objects. Therefore, the agent process reflects more on the dependencies of observed behaviors rather than on the inherent mechanisms by whi...
Interestingly, these two variants showed differences in their glycan composition with the full-length variant generally having less elaborated glycans than the truncated form (Fig. 2A, B). For example, the full-length form displays higher amounts of “immature” oligomannose glycoforms while the ...
(7.25)), the parametric form of the covariance makes direct calculation of the parameters difficult. Instead, we applied the expectation-maximization (EM) algorithm (Dempster et al., 1977), which iteratively updates the model parameters and latent factors until convergence is reached. The update ...
To further understand the similarities and differences between the molecular distributions generated by the GENiPPI framework and other models, we compared the distribution of molecular properties in the Testset, iPPI-DB inhibitor [72], and the generated molecular datasets from AAE, CharRNN, VAE, La...
(BP). The convolutional and pooling layers scan the entire pixel matrix in left-to-right and top-to-bottom directions, where the pooling layer can be in the form of Max, Min, and Average. As an example of a pixel matrix, the computation of the convolution layer and the maximum pooling...