Jae Oh Woo

According to our database, Jae Oh Woo authored at least 20 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2023

Active Learning in Bayesian Neural Networks with Balanced Entropy Learning Principle.

Jae Oh Woo

Proceedings of the Eleventh International Conference on Learning Representations, 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

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Unsupervised Contrastive Representation Learning for 3D Mesh Segmentation (Student Abstract).

Ayaan Haque, Hankyu Moon, Heng Hao, Sima Didari, Jae Oh Woo, Patrick Bangert

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

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

Analytic Mutual Information in Bayesian Neural Networks.

Jae Oh Woo

Proceedings of the IEEE International Symposium on Information Theory, 2022

2021

Entropy Inequalities for Sums in Prime Cyclic Groups.

Mokshay Madiman, Liyao Wang, Jae Oh Woo

SIAM J. Discret. Math., 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

PatchNet: Unsupervised Object Discovery based on Patch Embedding.

Hankyu Moon, Heng Hao, Sima Didari, Jae Oh Woo, Patrick Bangert

CoRR, 2021

BABA: Beta Approximation for Bayesian Active Learning.

Jae Oh Woo

CoRR, 2021

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

2019

Majorization and Rényi entropy inequalities via Sperner theory.

Mokshay Madiman, Liyao Wang, Jae Oh Woo

Discret. Math., 2019

2018

An Analytical Framework for Modeling a Spatially Repulsive Cellular Network.

Chang-Sik Choi, Jae Oh Woo, Jeffrey G. Andrews

IEEE Trans. Commun., 2018

2017

Discrete Entropy Power Inequalities via Sperner Theory.

Mokshay M. Madiman, Liyao Wang, Jae Oh Woo

CoRR, 2017

On the Steady State of Continuous Time Stochastic Opinion Dynamics.

Jae Oh Woo, François Baccelli, Sriram Vishwanath

CoRR, 2017

Modeling a Spatially Correlated Cellular Network with Strong Repulsion.

Chang-Sik Choi, Jae Oh Woo, Jeffrey G. Andrews

CoRR, 2017

On the coverage probability of a spatially correlated network.

Chang-Sik Choi, Jae Oh Woo, Jeffrey G. Andrews

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

2016

On the entropy and mutual information of point processes.

François Baccelli, Jae Oh Woo

Proceedings of the IEEE International Symposium on Information Theory, 2016

2015

A discrete entropy power inequality for uniform distributions.

Jae Oh Woo, Mokshay M. Madiman

Proceedings of the IEEE International Symposium on Information Theory, 2015

2014

Redundancy of Exchangeable Estimators.

Narayana P. Santhanam, Anand D. Sarwate, Jae Oh Woo

Entropy, 2014

A lower bound on the Rényi entropy of convolutions in the integers.

Liyao Wang, Jae Oh Woo, Mokshay M. Madiman

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014