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Found 11 papers, 4 papers with code
Learning a Patent-Informed Biomedical Knowledge Graph Reveals Technological Potential of Drug Repositioning Candidates
This study presents a novel protocol to comprehensively analyse various sources such as pharmaceutical patents and biomedical databases, and identify drug repositioning candidates with both technological potential and scientific evidence.
Accelerated materials language processing enabled by GPT
Finally, we develop an GPT-enabled extractive QA model, which provides improved performance and shows the possibility of automatically correcting annotations.
Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry
Second, we investigate how the geometric structure changes based on text conditioning in Stable Diffusion.
Generative Modeling through the Semi-dual Formulation of Unbalanced Optimal Transport
In this paper, we propose a novel generative model based on the semi-dual formulation of Unbalanced Optimal Transport (UOT).
Finding the global semantic representation in GAN through Frechet Mean
This semantic basis represents sample-independent meaningful perturbations that change the same semantic attribute of an image on the entire latent space.
Time-aware topic identification in social media with pre-trained language models: A case study of electric vehicles
Recent extensively competitive business environment makes companies to keep their eyes on social media, as there is a growing recognition over customer languages (e. g., needs, interests, and complaints) as source of future opportunities.
Analyzing the Latent Space of GAN through Local Dimension Estimation
In this paper, we approach this problem through a geometric analysis of latent spaces as a manifold.
Do Not Escape From the Manifold: Discovering the Local Coordinates on the Latent Space of GANs
The global warpage implies that the latent space is not well-aligned globally and therefore the global traversal directions are bound to show limited success on it.
Deep learning-based citation recommendation system for patents
In this study, we address the challenges in developing a deep learning-based automatic patent citation recommendation system.
Discond-VAE: Disentangling Continuous Factors from the Discrete
To represent these generative factors of data, we introduce two sets of continuous latent variables, private variable and public variable.
Attention routing between capsules
We replace the dynamic routing and squash activation function of the capsule network with dynamic routing (CapsuleNet) with the attention routing and capsule activation.
