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The Latent Space


Latent space decomposition into task-specific and domain-specific ...

In this study, we propose a novel method of acquiring the latent space (composed of task-specific and domain-specific subspaces) of data.

Quantum anomaly detection in the latent space of proton collision ...

In this work, we propose a strategy for anomaly detection tasks at the LHC based on unsupervised quantum machine learning, and demonstrate its effectiveness in ...

SpaceFusion: Structuring the unstructured latent space ... - Microsoft

SpaceFusion, a learning paradigm to align these different latent spaces—arrange and mix them smoothly like the paint on a palette—so AI can ...

About Us - Latent Space

Latent Space was born from a passion for blending technology with artistry. We believe that every memory holds a story, and our mission is to transform those ...

Phys. Rev. Materials 8, 103804 (2024) - Latent space active learning ...

Latent space active learning with message passing neural network: The case of H f O 2 · Xinjian Ouyang, Zhilong Wang, Xiao Jie, Feng Zhang, ...

On the Direct Alignment of Latent Spaces

Our experiments show that aligning the latent space with a linear transformation performs best while not needing more prior knowledge.

The Latent Space, infinite worlds? - Exploring AI

What is the Latent Space? The latent space appears as an infinite realm where anything and everything seems to be possible. It is where creative ...

Weak-form latent space dynamics identification - ScienceDirect.com

We introduce WLaSDI: Weak form Latent Space Dynamics Identification, a data-driven simulation framework that leverages WENDy: Weak form Parameter Estimation.

Latent and Embedding Space | Baeldung on Computer Science

'Latent space' and 'Embedding space' are vector spaces that help us obtain the essence of our data without getting lost in other unnecessary information.

Latent Space | Art UK

Latent Space by Jake Elwes (b.1993), 2017–2021, from City of London Corporation.

Analysis of Latent Space Representations for Object Detection

Deep Neural Networks (DNNs) successfully perform object detection tasks, and the Con- volutional Neural Network (CNN) backbone is a commonly used feature ...

Modeling Sentences in the Latent Space - ACL Anthology

Weiwei Guo and Mona Diab. 2012. Modeling Sentences in the Latent Space. In Proceedings of the 50th Annual Meeting of the Association for Computational ...

Using deep LSD to build operators in GANs latent space ... - PLOS

Here we propose a method to build a set of linearly independent vectors in the latent space of a trained GAN, which we call quasi-eigenvectors.

Deep Learning in Latent Space for Video Prediction and Compression

The most influential approaches adopt deep neural networks (DNNs) to remove spatial and temporal redundancies by finding the appropriate lower-dimensional ...

uwdata/latent-space-cartography: Visual analysis of vector ... - GitHub

Latent Space Cartography (LSC) is a visual analysis tool for mapping and comparing meaningful "semantic" dimensions in latent spaces. This repository contains ...

What about the Latent Space? The Need for Latent Feature Saliency ...

Saliency methods are designed to provide explainability for deep image processing models by assigning feature-wise importance scores and ...

Latent space visualization — Deep Learning bits #2 - HackerNoon

The latent space contains a compressed representation of the image, which is the only information the decoder is allowed to use to try to ...

Browsing the Latent Space: A New Approach to Interactive Design ...

By visualizing and interpreting the abstract space in which the outputs produced by generative systems operate (the latent space), users gain a ...

Activating Latent Space in Large Language Models - LinkedIn

This article explains the intricacies of latent space in LLMs and how it can be effectively activated through prompt engineering.

250k downloads of Latent Space Pod - Swyx

I last talked about my Latent Space adventures in [April](https://www.swyx.io/ranking-1-on-hn-in-mid-april) and [last ...