A lower bound on the Rényi entropy of convolutions in the integers. - Liyao Wang; Jae Oh Woo; Mokshay M. Madiman (ISIT, 2014)

Redundancy of Exchangeable Estimators. - Narayana P. Santhanam; Anand D. Sarwate; Jae Oh Woo (Entropy, 2014)

A discrete entropy power inequality for uniform distributions. - Jae Oh Woo; Mokshay M. Madiman (ISIT, 2015)

On the entropy and mutual information of point processes. - François Baccelli; Jae Oh Woo (ISIT, 2016)

On the coverage probability of a spatially correlated network. - Chang-Sik Choi; Jae Oh Woo; Jeffrey G. Andrews (ISIT, 2017)

Modeling a Spatially Correlated Cellular Network with Strong Repulsion. - Chang-Sik Choi; Jae Oh Woo; Jeffrey G. Andrews (CoRR, 2017)

On the Steady State of Continuous Time Stochastic Opinion Dynamics. - Jae Oh Woo; François Baccelli; Sriram Vishwanath (CoRR, 2017)

Discrete Entropy Power Inequalities via Sperner Theory. - Mokshay M. Madiman; Liyao Wang; Jae Oh Woo (CoRR, 2017)

An Analytical Framework for Modeling a Spatially Repulsive Cellular Network. - Chang-Sik Choi; Jae Oh Woo; Jeffrey G. Andrews (IEEE Trans. Commun., 2018)

Majorization and Rényi entropy inequalities via Sperner theory. - Mokshay Madiman; Liyao Wang; Jae Oh Woo (Discret. Math., 2019)

Highly Efficient Representation and Active Learning Framework for Imbalanced Data and its Application to COVID-19 X-Ray Classification. - Heng Hao; Sima Didari; Jae Oh Woo; Hankyu Moon; Patrick Bangert (CoRR, 2021)

BABA: Beta Approximation for Bayesian Active Learning. - Jae Oh Woo (CoRR, 2021)

PatchNet: Unsupervised Object Discovery based on Patch Embedding. - Hankyu Moon; Heng Hao; Sima Didari; Jae Oh Woo; Patrick Bangert (CoRR, 2021)

On the steady state of continuous-time stochastic opinion dynamics with power-law confidence. - François Baccelli; Sriram Vishwanath; Jae Oh Woo (J. Appl. Probab., 2021)

Entropy Inequalities for Sums in Prime Cyclic Groups. - Mokshay Madiman; Liyao Wang; Jae Oh Woo (SIAM J. Discret. Math., 2021)

Analytic Mutual Information in Bayesian Neural Networks. - Jae Oh Woo (ISIT, 2022)

Self-Supervised Contrastive Representation Learning for 3D Mesh Segmentation. - Ayaan Haque; Hankyu Moon; Heng Hao; Sima Didari; Jae Oh Woo; Patrick Bangert (CoRR, 2022)

Unsupervised Contrastive Representation Learning for 3D Mesh Segmentation (Student Abstract). - Ayaan Haque; Hankyu Moon; Heng Hao; Sima Didari; Jae Oh Woo; Patrick Bangert (AAAI, 2023)

Unsupervised Accuracy Estimation of Deep Visual Models using Domain-Adaptive Adversarial Perturbation without Source Samples. - JoonHo Lee; Jae Oh Woo; Hankyu Moon; Kwonho Lee (ICCV, 2023)

Active Learning in Bayesian Neural Networks with Balanced Entropy Learning Principle. - Jae Oh Woo (ICLR, 2023)

Improving Instruction Following in Language Models through Proxy-Based Uncertainty Estimation. - JoonHo Lee; Jae Oh Woo; Juree Seok; Parisa Hassanzadeh; Wooseok Jang; JuYoun Son; Sima Didari; Baruch Gutow; Heng Hao; Hankyu Moon; Wenjun Hu; Yeong-Dae Kwon; et al. (ICML, 2024)

Bayesian Active Learning for Semantic Segmentation. - Sima Didari; Wenjun Hu; Jae Oh Woo; Heng Hao; Hankyu Moon; Seungjai Min (CoRR, 2024)