- Image watermarking for Machine Learning datasets: Using SVD based image watermarking techniques to watermark numerical ML datasets
- How do different explanation presentation strategies of feature and data attribution techniques affect non-expert understanding?: Explaining Deep Learning models for Fact-Checking
- Finding Shortcuts to a black-box model using Frequent Sequence Mining: Explaining Deep Learning models for Fact-Checking
- A Comparison of Instance Attribution Methods: Comparing Instance Attribution Methods to Baseline k-Nearest Neighbors Method
- Algal Bloom Forecasting using Remote Sensing: Discovering the most predictive data modalities for Algal Bloom Forecasting
- Detecting Concept Drift in Deployed Machine Learning Models: How well do Margin Density-based concept drift detectors identify concept drift in case of synthetic/real-world data?
- Detect the watermark through the training model: A watermarking scheme to protect numerical classification datasets
- How Well do Clustering Similarities-Based Concept Drift Detectors Identify Drift in case of Synthetic/Real-World Data?