Results 231 to 240 of about 38,613 (267)

A Generative Neuro‐Symbolic AI for Protein Sequence Design

open access: yesAdvanced Science, EarlyView.
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne   +12 more
wiley   +1 more source

TriSAM: Tri-Plane SAM for Zero-Shot Cortical Blood Vessel Segmentation in VEM Images. [PDF]

open access: yesIEEE J Biomed Health Inform
Wan J   +8 more
europepmc   +1 more source

Zero-shot performance of selected large language and multimodal models on the 2023 Brazilian Portuguese medical residency exam. [PDF]

open access: yesSci Rep
Truyts CAM   +9 more
europepmc   +1 more source

Assessing personality using zero-shot generative AI scoring of brief open-ended text. [PDF]

open access: yesNat Hum Behav
Wright AGC   +6 more
europepmc   +1 more source

Zero-shot medical event prediction using a generative pretrained transformer on electronic health records. [PDF]

open access: yesJ Am Med Inform Assoc
Redekop E   +9 more
europepmc   +1 more source
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Spherical Zero-Shot Learning

IEEE Transactions on Circuits and Systems for Video Technology, 2022
Zero-shot Learning (ZSL) is a highly non-trivial task to generalize from seen to unseen classes. In this paper, we propose spherical zero-shot learning (SZSL) to address the major challenges in ZSL. By decoupling the similarity metric in the spherical embedding space into radius and angle, our SZSL can map classes to hyperspherical surfaces of ...
Jiayi Shen   +3 more
openaire   +1 more source

Zero-Shot Hyperspectral Sharpening

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023
Fusing hyperspectral images (HSIs) with multispectral images (MSIs) of higher spatial resolution has become an effective way to sharpen HSIs. Recently, deep convolutional neural networks (CNNs) have achieved promising fusion performance. However, these methods often suffer from the lack of training data and limited generalization ability.
Renwei Dian, Anjing Guo, Shutao Li 0001
openaire   +2 more sources

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