Here is a list of papers that I have worked on:
- Deep Learning Interpretation: Flip Points and Homotopy Methods, Mathematical and Scientific Machine Learning Conference, Proceedings of Machine Learning Research, 2020.
- Auditing and Debugging Deep Learning Models via Decision Boundaries: Individual-level and Group-level Analysis, La Matematica, Official Journal of the Association for Women in Mathematics, 2021.
- Learning Diverse Gaussian Graphical Models and Interpreting Edges, Proceedings of SIAM International Conference on Data Mining, 2019.
- Deep Learning Generalization and the Convex Hull of Training Sets, Deep Learning through Information Geometry Workshop, NeurIPS, 2020. (Invited to Springer Journal on Information Geometry)
- Extrapolation Frameworks in Cognitive Psychology Suitable for Study of Image Classification Models, Workshop on Human and Machine Decisions, NeurIPS, 2021.
- To What Extent Should We Trust AI Models When They Extrapolate? under review, 2022.
- Decision Boundaries and Convex Hulls in the Feature Space that Deep Learning Functions Learn From Images, 2022.
- A Homotopy Algorithm for Optimal Transport, 12th Annual Workshop on Optimization for Machine Learning, NeurIPS, 2020.
- Using Wavelets and Spectral Methods to Study Patterns in Image-Classification Datasets
- Debugging Trained Machine Learning Models Using Flip Points, ICLR Workshop on Debugging Trained Machine Learning Models, 2019.
- Interpretable Insights about Medical Image Datasets: Using Wavelets and Spectral Methods, ICML Workshop on Human Interpretability in Machine Learning, 2020.
- Social Fairness, Accountability and Transparency of the Data Economy: Using Machine Learning to Combat the Emptiness of Privacy Policies, ICML Workshop on Law & Machine Learning, 2020.
- A Sketching Method for Finding the Closest Point on a Convex Hull, 2021.
- Federated Learning without Revealing the Decision Boundaries, work in progress, 2021.
- Using Wavelets to Analyze Similarities in Image-Classification Datasets, 2020.
- Investigating Decision Boundaries of Trained Neural Networks
- Refining the Structure of Neural Networks Using Matrix Conditioning
- Optimizing Real-time Decisions in Hierarchical Humanitarian Aid Delivery Systems
- A Probabilistic Framework and a Homotopy Method for Real-time Hierarchical Freight Dispatch Decisions