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Found 13 papers, 7 papers with code
SeNM-VAE: Semi-Supervised Noise Modeling with Hierarchical Variational Autoencoder
We employ our method to generate paired training samples for real-world image denoising and super-resolution tasks.
The Robust Semantic Segmentation UNCV2023 Challenge Results
This paper outlines the winning solutions employed in addressing the MUAD uncertainty quantification challenge held at ICCV 2023.
Epsilon*: Privacy Metric for Machine Learning Models
We introduce Epsilon*, a new privacy metric for measuring the privacy risk of a single model instance prior to, during, or after deployment of privacy mitigation strategies.
Efficient Pattern-based Static Analysis Approach via Regular-Expression Rules
Second, we evaluate Codegex in automated code review by running it on 4256 PRs where it generated 372 review comments and received 116 feedback.
AIM 2022 Challenge on Instagram Filter Removal: Methods and Results
This paper introduces the methods and the results of AIM 2022 challenge on Instagram Filter Removal.
EasyRec: An easy-to-use, extendable and efficient framework for building industrial recommendation systems
We present EasyRec, an easy-to-use, extendable and efficient recommendation framework for building industrial recommendation systems.
Learn from Unpaired Data for Image Restoration: A Variational Bayes Approach
Current approaches aim at generating synthesized training data from unpaired samples by exploring the relationship between the corrupted and clean data.
Learning From Unpaired Data: A Variational Bayes Approach
Collecting the paired training data is a difficult task in practice, but the unpaired samples broadly exist.
Cross-domain error minimization for unsupervised domain adaptation
Unsupervised domain adaptation aims to transfer knowledge from a labeled source domain to an unlabeled target domain.
An Unsupervised Deep Learning Approach for Real-World Image Denoising
In the real-world case, the noise distribution is so complex that the simplified additive white Gaussian (AWGN) assumption rarely holds, which significantly deteriorates the Gaussian denoisers' performance.
Field-Tuned Quantum Effects in a Triangular-Lattice Ising Magnet
We report thermodynamic and neutron scattering measurements of the triangular-lattice quantum Ising magnet TmMgGaO 4 in longitudinal magnetic fields.
Strongly Correlated Electrons Materials Science
Learning transferable and discriminative features for unsupervised domain adaptation
In this paper, a novel method called \textit{learning TransFerable and Discriminative Features for unsupervised domain adaptation} (TFDF) is proposed to optimize these two objectives simultaneously.
Dual Adversarial Domain Adaptation
Recent experiments have shown that when the discriminator is provided with domain information in both domains and label information in the source domain, it is able to preserve the complex multimodal information and high semantic information in both domains.
Ranked #5 on
Domain Adaptation
on ImageCLEF-DA
