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Found 17 papers, 4 papers with code
NonSTOP: A NonSTationary Online Prediction Method for Time Series
Moreover, since these transformations are usually unknown, we employ the learning with experts setting to develop a fully online method (NonSTOP-NonSTationary Online Prediction) for predicting nonstationary time series.
Risks of Using Non-verified Open Data: A case study on using Machine Learning techniques for predicting Pregnancy Outcomes in India
As a result, we can often end up using data that is not representative of the problem we are trying to solve.
privGAN: Protecting GANs from membership inference attacks at low cost
It has been shown that such synthetic data can be used for a variety of downstream tasks such as training classifiers that would otherwise require the original dataset to be shared.
MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models
In this work, we propose the first formal framework for membership privacy estimation in generative models.
Machine Learning for Glacier Monitoring in the Hindu Kush Himalaya
Glacier mapping is key to ecological monitoring in the hkh region.
Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary
We show that by using the FELICIA mechanism, a data owner with limited image samples can generate high-quality synthetic images with high utility while neither data owners has to provide access to its data.
Height Estimation of Children under Five Years using Depth Images
Malnutrition is a global health crisis and is the leading cause of death among children under five.
A machine learning pipeline for aiding school identification from child trafficking images
Child trafficking in a serious problem around the world.
An Analysis of the Deployment of Models Trained on Private Tabular Synthetic Data: Unexpected Surprises
Diferentially private (DP) synthetic datasets are a powerful approach for training machine learning models while respecting the privacy of individual data providers.
Retinal Microvasculature as Biomarker for Diabetes and Cardiovascular Diseases
Conclusion: In the case of DR, most of the disease biomarkers are related topologically to the vasculature.
Interpretable and Explainable Machine Learning for Materials Science and Chemistry
While the uptake of data-driven approaches for materials science and chemistry is at an exciting, early stage, to realise the true potential of machine learning models for successful scientific discovery, they must have qualities beyond purely predictive power.
An Artificial Intelligence Dataset for Solar Energy Locations in India
Using this dataset, we measure the solar footprint across India and quantified the degree of landcover modification associated with the development of PV infrastructure.
BankNote-Net: Open dataset for assistive universal currency recognition
This last task, the recognition of banknotes from different denominations, has been addressed by the use of computer vision models for image recognition.
Dwelling Type Classification for Disaster Risk Assessment Using Satellite Imagery
Then a risk score assessment model was employed, using the determined dwelling type along with an inundation model of the regions.
Poverty rate prediction using multi-modal survey and earth observation data
This work presents an approach for combining household demographic and living standards survey questions with features derived from satellite imagery to predict the poverty rate of a region.
Assessment of Differentially Private Synthetic Data for Utility and Fairness in End-to-End Machine Learning Pipelines for Tabular Data
To the best of our knowledge, our work is the first that: (i) proposes a training and evaluation framework that does not assume that real data is available for testing the utility and fairness of machine learning models trained on synthetic data; (ii) presents the most extensive analysis of synthetic data set generation algorithms in terms of utility and fairness when used for training machine learning models; and (iii) encompasses several different definitions of fairness.
Multimodal Foundation Models for Zero-shot Animal Species Recognition in Camera Trap Images
In particular, we instruction tune vision-language models to generate detailed visual descriptions of camera trap images using similar terminology to experts.
