Results 51 to 60 of about 65,539 (306)
Leveraging diffusion models for unsupervised out-of-distribution detection on image manifold
Frontiers in Artificial IntelligenceOut-of-distribution (OOD) detection is crucial for enhancing the reliability of machine learning models when confronted with data that differ from their training distribution.
Zhenzhen Liu +2 more
doaj +1 more source
Predicting cellular responses to complex perturbations in high‐throughput screens
Molecular Systems Biology, 2023 Recent advances in multiplexed single‐cell transcriptomics experiments facilitate the high‐throughput study of drug and genetic perturbations. However, an exhaustive exploration of the combinatorial perturbation space is experimentally unfeasible ...
Mohammad Lotfollahi +18 more
doaj +1 more source
Decontextualized learning for interpretable hierarchical representations of visual patterns
Patterns, 2021 Summary: Apart from discriminative modeling, the application of deep convolutional neural networks to basic research utilizing natural imaging data faces unique hurdles.
Robert Ian Etheredge +2 more
doaj +1 more source
The rules behind - tutorial on generative modeling
, 2015 This tutorial introduces the concepts and techniques of generative modeling. It starts with some introductory examples in the first learning unit to motivate the main idea: to describe a shape using an algorithm. After the explanation of technical terms,
Krispel, Ulrich +2 more
core +1 more source
Fairness in generative modeling
, 2022 International audienceWe design general-purpose algorithms for addressing fairness issues and mode collapse in generative modeling. More precisely, to design fair algorithms for as many sensitive variables as possible, including variables we might not be
Hosu, Vlad +13 more
core +1 more source
Learning With Imbalanced Data in Smart Manufacturing: A Comparative Analysis
IEEE Access, 2021 The Internet of Things (IoT) paradigm is revolutionising the world of manufacturing into what is known as Smart Manufacturing or Industry 4.0. The main pillar in smart manufacturing looks at harnessing IoT data and leveraging machine learning (ML) to ...
Yasmin Fathy +2 more
doaj +1 more source
Modelling control in generation [PDF]
Proceedings of the Eleventh European Workshop on Natural Language Generation - ENLG '07, 2007 In this paper we present a view of natural language generation in which the control structure of the generator is clearly separated from the content decisions made during generation, allowing us to explore and compare different control strategies in a systematic way.
Roger Evans +4 more
openaire +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Claudin‐6 has emerged as a promising immunotherapeutic target, yet protein‐level data in atypical teratoid/rhabdoid tumors (AT/RTs) have been inconsistent. We analyzed 36 well‐characterized AT/RT samples and found membranous claudin‐6 protein expression in 58% of cases, with striking enrichment in the molecular subgroup AT/RT‐TYR (100%) and ...
Victoria E. Fincke +4 more
wiley +1 more source
Generative Modeling with Neural Ordinary Differential Equations [PDF]
, 2019 Neural ordinary differential equations (NODEs) (Chen et al., 2018) are ordinary differential equations (ODEs) with their dynamics modeled by neural networks.
Dockhorn, Tim
core
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Wilms tumor (WT) treatment imposes a significant time burden on patients and their families. Time toxicity is a patient‐centered metric that quantifies the burden of healthcare interaction. We sought to define time toxicity in the first year after diagnosis of WT and hypothesized that it would increase as tumor stage and treatment ...
Caleb Q. Ashbrook +6 more
wiley +1 more source