Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 In this paper, we propose a new method to perform data augmentation in a reliable way in the High Dimensional Low Sample Size (HDLSS) setting using a geometry-based variational autoencoder (VAE).
Clément Chadebec +3 more
semanticscholar +1 more source
Sensors, 2022 Aiming at the problems of low fault diagnosis accuracy caused by insufficient samples and unbalanced data sample distribution in bearing fault diagnosis, this paper proposes a fault diagnosis method for rolling bearings referencing conditional deep ...
Cheng Peng, Shuting Zhang, Changyun Li
doaj +1 more source
SpecMix : A Mixed Sample Data Augmentation method for Training withTime-Frequency Domain Features [PDF]
Interspeech, 2021 A mixed sample data augmentation strategy is proposed to enhance the performance of models on audio scene classification, sound event classification, and speech enhancement tasks.
Gwantae Kim, D. Han, Hanseok Ko
semanticscholar +1 more source
FMix: Enhancing Mixed Sample Data Augmentation
, 2020 Code available at https://github.com/ecs-vlc ...
Harris, Ethan +5 more
openaire +2 more sources
Augmenting sampling based controllers with machine learning [PDF]
Proceedings of the ACM SIGGRAPH / Eurographics Symposium on Computer Animation, 2017 Efficient learning of 3D character control still remains an open problem despite of the remarkable recent advances in the field. We propose a new algorithm that combines planning by a sampling-based model-predictive controller and learning from the planned control, which is very noisy.
Hämäläinen, Perttu, Rajamäki, Joose
openaire +1 more source
Cotton Fusarium wilt diagnosis based on generative adversarial networks in small samples
Frontiers in Plant Science, 2023 This study aimed to explore the feasibility of applying Generative Adversarial Networks (GANs) for the diagnosis of Verticillium wilt disease in cotton and compared it with traditional data augmentation methods and transfer learning. By designing a model
Zhenghang Zhang +12 more
doaj +1 more source
Bayesian logistic regression for presence-only data [PDF]
, 2015 Presence-only data are referred to situations in which a censoring mechanism acts on a binary response which can be partially observed only with respect to one outcome, usually denoting the \textit{presence} of an attribute of interest. A typical example
Antti Pettinen +3 more
core +1 more source
Retrieve-and-Sample: Document-level Event Argument Extraction via Hybrid Retrieval Augmentation
Annual Meeting of the Association for Computational Linguistics, 2023 Recent studies have shown the effectiveness of retrieval augmentation in many generative NLP tasks. These retrieval-augmented methods allow models to explicitly acquire prior external knowledge in a non-parametric manner and regard the retrieved ...
Yubing Ren +5 more
semanticscholar +1 more source
Lifetime Bipolar Disorder comorbidity and related clinical characteristics in patients with primary Obsessive Compulsive Disorder: a report from the International College of Obsessive-Compulsive Spectrum Disorders (ICOCS) [PDF]
, 2019 IntroductionBipolar disorder (BD) and obsessive compulsive disorder (OCD) are prevalent, comorbid, and disabling conditions, often characterized by early onset and chronic course.
Benatti, Beatrice +20 more
core +4 more sources
Enhancement of psychosocial treatment with D-cycloserine: models, moderators, and future directions [PDF]
, 2016 Advances in the understanding of the neurobiology of fear extinction have resulted in the development of d-cycloserine (DCS), a partial glutamatergic N-methyl-D-aspartate agonist, as an augmentation strategy for exposure treatment.
de Kleine, Rianne A. +8 more
core +1 more source