Adaptive Nonparametric Variational Autoencoder. - Tingting Zhao; Zifeng Wang 002; Aria Masoomi; Jennifer G. Dy (CoRR, 2019)

Instance-wise Feature Grouping. - Aria Masoomi; Chieh Wu; Tingting Zhao; Zifeng Wang 002; Peter J. Castaldi; Jennifer G. Dy (NeurIPS, 2020)

Layer-wise Learning of Kernel Dependence Networks. - Chieh Wu; Aria Masoomi; Arthur Gretton; Jennifer G. Dy (CoRR, 2020)

Kernel Dependence Network. - Chieh Wu; Aria Masoomi; Arthur Gretton; Jennifer G. Dy (CoRR, 2020)

Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space. - Sandesh Ghimire; Aria Masoomi; Jennifer G. Dy (NeurIPS, 2021)

Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness. - Zifeng Wang 002; Tong Jian; Aria Masoomi; Stratis Ioannidis; Jennifer G. Dy (NeurIPS, 2021)

Improved prediction of smoking status via isoform-aware RNA-seq deep learning models. - Zifeng Wang 002; Aria Masoomi; Zhonghui Xu; Adel Boueiz; Sool Lee; Tingting Zhao; Russell Bowler; Michael H. Cho; Edwin K. Silverman; Craig P. Hersh; Jennifer G. Dy; Peter J. Castaldi (PLoS Comput. Biol., 2021)

Deep Layer-wise Networks Have Closed-Form Weights. - Chieh Tzu Wu; Aria Masoomi; Arthur Gretton; Jennifer G. Dy (AISTATS, 2022)

Explanations of Black-Box Models based on Directional Feature Interactions. - Aria Masoomi; Davin Hill; Zhonghui Xu; Craig P. Hersh; Edwin K. Silverman; Peter J. Castaldi; Stratis Ioannidis; Jennifer G. Dy (ICLR, 2022)

Analyzing the Effects of Classifier Lipschitzness on Explainers. - Zulqarnain Khan; Aria Masoomi; Davin Hill; Jennifer G. Dy (CoRR, 2022)

Explanation Uncertainty with Decision Boundary Awareness. - Davin Hill; Aria Masoomi; Sandesh Ghimire; Max Torop; Jennifer G. Dy (CoRR, 2022)

Inv-SENnet: Invariant Self Expression Network for clustering under biased data. - Ashutosh Singh; Ashish Singh; Aria Masoomi; Tales Imbiriba; Erik G. Learned-Miller; Deniz Erdogmus (CoRR, 2022)

Deep Bayesian Unsupervised Lifelong Learning. - Tingting Zhao; Zifeng Wang 002; Aria Masoomi; Jennifer G. Dy (Neural Networks, 2022)

Inv-Senet: Invariant Self Expression Network for Clustering Under Biased Data. - Ashutosh Singh; Ashish Singh; Aria Masoomi; Tales Imbiriba; Erik G. Learned-Miller; Deniz Erdogmus (ICASSP, 2023)

SmoothHess: ReLU Network Feature Interactions via Stein's Lemma. - Max Torop; Aria Masoomi; Davin Hill; Kivanç Köse; Stratis Ioannidis; Jennifer G. Dy (NeurIPS, 2023)

Divide and Compose with Score Based Generative Models. - Sandesh Ghimire; Armand Comas Massague; Davin Hill; Aria Masoomi; Octavia I. Camps; Jennifer G. Dy (CoRR, 2023)

Geometry of Score Based Generative Models. - Sandesh Ghimire; Jinyang Liu 005; Armand Comas Massague; Davin Hill; Aria Masoomi; Octavia I. Camps; Jennifer G. Dy (CoRR, 2023)

Boundary-Aware Uncertainty for Feature Attribution Explainers. - Davin Hill; Aria Masoomi; Max Torop; Sandesh Ghimire; Jennifer G. Dy (AISTATS, 2024)

Analyzing Explainer Robustness via Probabilistic Lipschitzness of Prediction Functions. - Zulqarnain Khan; Davin Hill; Aria Masoomi; Joshua T. Bone; Jennifer G. Dy (AISTATS, 2024)

Axiomatic Explainer Globalness via Optimal Transport. - Davin Hill; Joshua T. Bone; Aria Masoomi; Max Torop; Jennifer G. Dy (AISTATS, 2025)

OrdShap: Feature Position Importance for Sequential Black-Box Models. - Davin Hill; Brian L. Hill; Aria Masoomi; Vijay S. Nori; Robert E. Tillman; Jennifer G. Dy (CoRR, 2025)