Results 101 to 110 of about 13,735 (297)
Multivariate Variational Autoencoder
CoRRLearning latent representations that are simultaneously expressive, geometrically well-structured, and reliably calibrated remains a central challenge for Variational Autoencoders (VAEs). Standard VAEs typically assume a diagonal Gaussian posterior, which simplifies optimization but rules out correlated uncertainty and often yields entangled or ...
openaire +3 more sources
Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers
Advanced Science, EarlyView.FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao +9 more
wiley +1 more source
IEEE Access, 2020 Image interpolation is often implemented using one of two methods: optical flow or convolutional neural networks. These methods are typically pixel-based; they do not work well on objects between images far apart.
Paulino Cristovao +3 more
doaj +1 more source
Longitudinal Variational Autoencoder
, 2020 Peer ...
Ramchandran, Siddharth +4 more
openaire +4 more sources
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Advanced Science, EarlyView.Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
Variational Autoencoders for Collaborative Filtering [PDF]
Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18, 2018 10 pages, 3 figures.
Dawen Liang +3 more
openaire +2 more sources
PlantGFM: A Genomic Foundation Model for Discovery and Creation of Plant Genes
Advanced Science, EarlyView.A plant genomic foundation model pre‐trained on 12 species enables both accurate gene prediction and de novo gene design. Through AI‐human knowledge screening, seven designed sequences showed transcriptional activity in plants, with two expressing stable proteins—demonstrating the first DNA‐RNA‐protein expression of LLM‐generated genes in plants and ...
Changhao Li +10 more
wiley +1 more source
Topology‐Aware Deep Learning on Higher‐Order Structures for Drug Response Prediction
Advanced Science, EarlyView.We present TopDr, a topology‐aware deep learning framework that encodes both drugs and cell lines as multiscale simplicial complexes, capturing interactions at the 0‐, 1‐, and 2‐simplex levels. By jointly integrating local higher‐order neighborhoods and global topological structures, TopDr generates enriched representations for sensitivity prediction ...
Cong Shen +3 more
wiley +1 more source
Ladder Variational Autoencoder [PDF]
, 2016 Variational autoencoders are powerful models for unsupervised learning. However deep models with several layers of dependent stochastic variables are difficult totrain which limits the improvements obtained using these highly expressive models.
Sønderby, Casper Kaae +4 more
core
Advanced Science, EarlyView.This review explores the convergence of artificial intelligence technologies in modeling drug–drug and drug–target interactions. By evaluating advanced feature engineering, architectural innovations, and learning paradigms reveals shared evolutionary trends and critical challenges, such as cold‐start settings and shortcut learning.
Xin Sun, Tong Wang
wiley +1 more source