Heeyoung Kim
12 papers · 2016–2026 · 8 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+1 more ↓ Show less ↑
🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Half 🗺️ Taxonomy Completionist (23) 🐣 Hot Topic Early Bird 💎 Century Club · Bronze
📈
Trend Setter
Top co-authors
Research topics
Machine Learning
(9)
Artificial Intelligence
(5)
Learning Types
(5)
Core Methods
(4)
Optimization & Theory · Machine Learning
(4)
Deep Learning
(3)
Bayesian & Probabilistic · Artificial Intelligence
(3)
Bayesian & Probabilistic · Machine Learning
(3)
Learning Paradigms
(2)
Application Areas
(1)
Architectures
(1)
Models
(1)
Optimization & Theory · Deep Learning
(1)
Keywords
semi-supervised learning
(3)
out-of-distribution detection
(3)
class imbalance
(3)
uncertainty quantification
(2)
variational inference
(2)
representation learning
(2)
logit adjustment
(2)
gaussian process
(1)
few-shot learning
(1)
image classification
(1)
pseudo labeling
(1)
dynamic routing
(1)
bayesian optimization
(1)
hyperparameter optimization
(1)
fisher information matrix
(1)
gaussian processes
(1)
generalization ability
(1)
prior distribution
(1)
fisher information
(1)
bayesian inference
(1)
Papers
Nonlocal Bayesian Modeling of Continuous Spatio-Temporal Dynamics
UAI 2026
Learnable Logit Adjustment for Imbalanced Semi-Supervised Learning under Class Distribution Mismatch
ICCV 2025
CDMAD: Class-Distribution-Mismatch-Aware Debiasing for Class-Imbalanced Semi-Supervised Learning
CVPR 2024
Rebalancing Using Estimated Class Distribution for Imbalanced Semi-Supervised Learning under Class Distribution Mismatch
ECCV 2024
Uncertainty Estimation by Density Aware Evidential Deep Learning
ICML 2024
Inverse-Reference Priors for Fisher Regularization of Bayesian Neural Networks
AAAI 2023
ABC: Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning
NeurIPS 2021
Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models
NeurIPS 2021
Objective Bound Conditional Gaussian Process for Bayesian Optimization
ICML 2021
OOD-MAML: Meta-Learning for Few-Shot Out-of-Distribution Detection and Classification
NeurIPS 2020
Ladder Capsule Network
ICML 2019
Bayesian Nonparametric Collaborative Topic Poisson Factorization for Electronic Health Records-Based Phenotyping
IJCAI 2016