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Found 6 papers, 2 papers with code
Differentially Private Communication of Measurement Anomalies in the Smart Grid
In this paper, we present a framework based on differential privacy (DP) for querying electric power measurements to detect system anomalies or bad data.
Differential Privacy for Class-based Data: A Practical Gaussian Mechanism
In this paper, we present a notion of differential privacy (DP) for data that comes from different classes.
Solar Photovoltaic Systems Metadata Inference and Differentially Private Publication
Stakeholders in electricity delivery infrastructure are amassing data about their system demand, use, and operations.
Differentially Private $K$-means Clustering Applied to Meter Data Analysis and Synthesis
It is increasingly apparent that methods are required for allowing a variety of stakeholders to leverage the data in a manner that preserves the privacy of the consumers.
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
We present an algorithm addressing this problem, PULSE (Photo Upsampling via Latent Space Exploration), which generates high-resolution, realistic images at resolutions previously unseen in the literature.
Ranked #10 on
Image Super-Resolution
on FFHQ 256 x 256 - 4x upscaling
(PSNR metric)
New Techniques for Preserving Global Structure and Denoising with Low Information Loss in Single-Image Super-Resolution
This work identifies and addresses two important technical challenges in single-image super-resolution: (1) how to upsample an image without magnifying noise and (2) how to preserve large scale structure when upsampling.
