Research record
Publications
Peer-reviewed work in explainable AI, reliable learning, generative models, planning, time series, and statistical inference.
131papers in view
112026
192025
82024
122023
72022
132021
92020
62019
32018
42017
82016
122015
52014
22013
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22011
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131 of 131 publications
2026
Unified Backbone Refinement for Diffusion Models via Internal-Latent Analysis
Diffusion Integrated Gradients: Controllable Path Generation for Flexible Feature Attribution
SPICE: Simple Polysemantic Feature Interpretation via Clustering-based Explanations
Spectral Integrated Gradients for Coarse-to-Fine Feature Attribution
DistMatch: Adaptive Binning via Distribution Matching for Robust Sequential Conformal Prediction
Breaking the Lock-in: Diversifying Text-to-Image Generation via Representation Modulation
Manifold-Aligned Guided Integrated Gradients for Reliable Feature Attribution
Incomplete Prompt Jailbreaks in Large Language Models
K-MetBench: A Multi-Dimensional Benchmark for Fine-Grained Evaluation of Expert Reasoning, Locality, and Multimodality in Meteorology
Towards Transparent Time Series Analysis: Exploring Methods and Enhancing Interpretability
2025
State-Covering Trajectory Stitching for Diffusion Planners
On the Relationship between Populated Regions and Adversarial Robustness in Deep Neural Networks
When Format Changes Meaning: Investigating Semantic Inconsistency of Large Language Models
Unsupervised Concept Discovery for Deep Weather Forecast Models with High-Resolution Radar Data
Amortized Baseline Selection via Rank-Revealing QR for Efficient Model Explanation
Deep-DFVAR: Dynamic Factor Vector Autoregression with Deep Learning for Regional House Price Index Forecasting
Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations
Context-aware Negative Sampling for Sequential Recommendation
Example-Based Concept Analysis Framework for Deep Weather Forecast Models
Counterfactual Activation Editing for Post-hoc Prosody and Mispronunciation Correction in TTS Models
Deontological Keyword Bias: The Impact of Modal Verbs on Normative Judgments of Language Models
Local Manifold Approximation and Projection for Manifold-Aware Diffusion Planning
Enhancing Creative Generation on Stable Diffusion-based Models
An Automated Method to Correct Artifacts in Neural Text-to-Speech Models
A Perspective on Foundation Models in Chemistry
Rethinking Shapley Value for Negative Interactions in Non-convex Games
Neural ODE Transformers: Analyzing Internal Dynamics and Adaptive Fine-tuning
xPatch: Dual-Stream Time Series Forecasting with Exponential Seasonal-Trend Decomposition
Diverse Rare Sample Generation with Pretrained GANs
2024
LoCo: Low-rank Compositional Rotation Fine-tuning
Towards Dynamic Trend Filtering through Trend Point Detection with Reinforcement Learning
Memorizing Documents with Guidance in Large Language Models
Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions
Pathwise Explanation of ReLU Neural Networks
Towards Diverse Perspective Learning with Select over Multiple Temporal Poolings
Understanding Distributed Representations of Concepts in Deep Neural Networks without Supervision
Capsule Neural Networks as Noise Stabilizer for Time Series Data
2023
멀티 에이전트 강화학습에서의 게이트 기반 메시지 교환
Impact of Co-occurrence on Factual Knowledge of Large Language Models
CR-COPEC: Causal Rationale of Corporate Performance Changes to learn from Financial Reports
SigFormer: Signature Transformers for Deep Hedging
Refining Diffusion Planner for Reliable Behavior Synthesis by Automatic Detection of Infeasible Plans
Implicit Contrastive Representation Learning with Guided Stop-gradient
Explainable AI-Based Interface System for Weather Forecasting Model
Beyond Single Path Integrated Gradients for Reliable Input Attribution via Randomized Path Sampling
Variational Curriculum Reinforcement Learning for Unsupervised Discovery of Skills
Rarity Score : A New Metric to Evaluate the Uncommonness of Synthesized Images
Adaptive and Explainable Deployment of Navigation Skills via Hierarchical Deep Reinforcement Learning
Capsule Neural Networks as Noise Stabilizer for Time Series Data
2022
South Korea’s Response to Surging AI Use in the US and China
Learning Fractional White Noises in Neural Stochastic Differential Equations
Distilled Gradient Aggregation: Purify Features for Input Attribution in the Deep Neural Network
Can We Find Neurons that Cause Unrealistic Images in Deep Generative Networks?
An Unsupervised Way to Understand Artifact Generating Internal Units in Generative Neural Networks
Cooperative Multi-Robot Task Allocation with Reinforcement Learning
Scheduling PID Attitude and Position Control Frequencies for Time-Optimal Quadrotor Waypoint Tracking under Unknown External Disturbances
2021
Lifted Inference for Hybrid Relational Models
Lifted Aggregation and Skolemization for Directed Models
Predicting Potentially Hazardous Chemical Reactions Using Explainable Neural Network
Explaining the Decisions of Deep Policy Networks for Robotic Manipulations
Semi-Supervised Training of Deep Generative Models for High-Dimensional Anomaly Detection
Word sense disambiguation based on context selection using knowledge-based word similarity
Interpreting Internal Activation Patterns in Deep Temporal Neural Networks by Finding Prototypes
Conditional Temporal Neural Processes with Covariance Loss
Automatic Correction of Internal Units in Generative Neural Networks
Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior
Characterizing Deep Gaussian Processes via Nonlinear Recurrence Systems
Interpreting Deep Neural Networks with Relative Sectional Propagation by Analyzing Comparative Gradients and Hostile Activations
Spatiotemporal characterization of GPCR activity and function during endosomal trafficking pathway
2020
Visualization of autophagy progression by Red-Green-Blue autophagy sensor
Interpreting and Explaining Deep Neural Networks: A Perspective on Time Series Data
Improved Predictive Deep Temporal Neural Networks with Trend Filtering
HetPipe: Enabling Large DNN Training on (Whimpy) Heterogeneous GPU Clusters through Integration of Pipelined Model Parallelism and Data Parallelism
A Single Multi-Task Deep Neural Network with Post-Processing for Object Detection with Reasoning and Robotic Grasp Detection
An Efficient Explorative Sampling Considering the Generative Boundaries of Deep Generative Neural Networks
Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networks
시계열 심층학습 모델의 은닉 노드에 대한 시각화
섀플리 값 추정을 이용한 주가 변화 원인 설명 문장 분류 모델 분석
2019
XAI—Explainable artificial intelligence
Markov Information Bottleneck to Improve Information Flow in Stochastic Neural Networks
Confirmatory Bayesian Online Change Point Detection in the Covariance Structure of Gaussian Processes
Discovering Latent Covariance Structure for Multiple Time Series
Implementation of End-to-End Training of Deep Visuomotor Policies for Manipulation of a Robotic Arm of Baxter Research Robot
백스터 로봇의 시각기반 로봇 팔 조작 딥러닝을 위한 강화학습 알고리즘 구현
2018
2017
Generative Design of Electromagnetic Structures Through Bayesian Learning
Expanding Statistical Similarity Based Data Reduction to Capture Diverse Patterns
Learning Execution Contexts from System Call Distribution for Anomaly Detection in Smart Embedded System
Improving Statistical Similarity Based Data Reduction for Non-Stationary Data
2016
Global Deconvolutional Networks for Semantic Segmentation
Novel Data Reduction Based on Statistical Similarity
Improving Imprecise Compressive Sensing Models
Automatic Construction of Nonparametric Relational Regression Models for Multiple Time Series
지식베이스 확장을 위한 자동 관계 추출
분산환경에서의 기계학습
딥러닝 기반 실시간 안개제거 알고리즘
인공지능시대와 제4차 산업혁명
2015
Extracting Baseline Electricity Usage Using Gradient Tree Boosting
Reading Documents for Bayesian Online Change Point Detection
A Scalable and Flexible Repository for Big Sensor Data
A Deterministic Partition Function Approximation for Exponential Random Graph Models
Memory Heat Map: Anomaly Detection in Real-Time Embedded Systems Using Memory Behavior
Best Predictive Generalized Linear Mixed Model with Predictive Lasso for High-Speed Network Data Analysis
Learning Compressive Sensing Models for Big Spatio-Temporal Data
Learning Relational Kalman Filtering
Semi-Local Structure Patterns for Robust Face Detection
딥러닝 이론과 응용
머신러닝(Machine Learning)
다양한 머신러닝 알고리즘
2014
2013
2012
2011
2009
2008
Spatio-Temporal Pyramid Matching for Sports Videos
Virtual Sensor-Powered Spatiotemporal Aggregation and Transformation: A Case Study Analyzing Near-Real-Time NEXRAD and Precipitation Gage Data in a Digital Watershed
2005
Efficient navigation of mobile robot based on the robot’s experience in human co-existing environment