Lab Seminar

Lab Seminar Multiple Imputation for Missing Data

Presenter: 이희윤 · Keywords: #imputation #Statistics

Paper Review A Deep-Learning-Based Surrogate Model for Thermal Signature Prediction in Laser Metal Deposition (IEEE T-ASE 2023)

Presenter: Yongmin Kim · Keywords: #DeepLearning #QualityMonitoring #GAN

Paper Review Neural Network Control Chart for Autocorrelated Multivariate Data (Quality Engineering)

Presenter: 유정우 · Keywords: #QualityMonitoring #ControlChart

Paper Review Autoencoding Under Normalization Constraints (PMLR, 2021)

Presenter: SeungSu Kam · Keywords: #Anomaly Detection #Autoencoder

Paper Review Uncertainty quantification in digital twin (SMO 2023)

Presenter: 전병훈 · Keywords: #Uncertainty Estimation

Paper Review Multimodal Industrial Anomaly Detection via Hybrid Fusion (CVPR, 2023)

Presenter: SeungSu Kam · Keywords: #Anomaly Detection #multi-modal learning

Paper Review Bayesian Calibration of Computer Models (JRSS:B 2001)

Presenter: Chanbeom · Keywords: #Statistics

Paper Review ANOMALY TRANSFORMER: TIME SERIES ANOMALY DETECTION WITH ASSOCIATION DISCREPANCY (ICLR 2022 Spotlight)

Presenter: SeungSu Kam · Keywords: #Time-series anomaly detection #Transformer

Lab Seminar Understanding Complex Missingness Mechanisms

Presenter: 이시은 · Keywords: #imputation #missingness data

Lab Seminar KAN: Kolmogorov–Arnold Networks (ICLR 2025)

Presenter: Chanbeom · Keywords: #Deep Learning

Paper Review TIME-LLM: Reprogramming LLMs for Time Series Forecasting

Presenter: Seongjin · Keywords: #LLM #time series

Lab Seminar MTSCI: A Conditional Diffusion Model for Multivariate Time Series Consistent Imputation (CIKM 2024)

Presenter: 이희윤 · Keywords: #DeepLearning #time series #Diffusion Model

Paper Review Linear-Time Sequence Modeling with Selective State Spaces (COLM 2024)

Presenter: 전병훈 · Keywords: #State space model #time series #RNN

Lab Seminar CARLA: Self-supervised contrastive representation learning for time series anomaly detection (Pattern Recognition 2025)

Presenter: Yongmin Kim · Keywords: #Contrastive learning #Self-supervised Learning #Time-series anomaly detection #Anormaly Injection

Paper Review Neural SDEs as Infinite-Dimensional GANs (PMLR, 2021)

Presenter: SeungSu Kam · Keywords: #Neural Differential Equation #Generative Model

Lab Seminar Root Cause Analysis of anomalies in multivariate time series through granger causal discovery (ICLR 2025)

Presenter: 강태원 · Keywords: #Autoencoder #Causality #Anomaly Detection

Lab Seminar Current Research Topics in Survival Analysis

Presenter: Chanbeom · Keywords: #Survival Analysis

Paper Review Trajectory Flow Matching with Applications to Clinical Time Series Modelling (NeurIPS 2024)

Presenter: Jae Hun Cho · Keywords: #Irregular time series #Flow Matching #Clinical time series

Paper Review Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series (KDD 2023)

Presenter: Hyejin Cho · Keywords: #Attention #Transformer #Irregular time series #Warping

Paper Review Neural Frailty Machine: Beyond proportional hazard assumption in neural survival regressions (NeurIPS 2023)

Presenter: Chanbeom · Keywords: #Survival Analysis #Deep Learning

Paper Review ClimODE: Climate and Weather Forecasting with Physics-Informed Neural ODEs (ICLR 2024)

Presenter: 전병훈 · Keywords: #Neural Differential Equation #Physics-Informed

Lab Seminar Multi-Time Attention Networks for Irregularly Sampled Time Series (mTANs)

Presenter: 이시은 · Keywords: #Irregular time series #Attention

Paper Review Modulated Neural ODEs (NeurIPS 2023)

Presenter: Yongmin Kim · Keywords: #Neural Differential Equation

Paper Review Physics-Informed Neural ODE with Heterogeneous Control Inputs (PINOHI) for Quality Prediction of Composite Adhesive Joints

Presenter: Seongjin · Keywords: #Neural Differential Equation #Physics-Informed

Paper Review PREVENT : An Unsupervised Approach to Predict Software Failures in Production (IEEE Trans. Softw. Eng. 2025)

Presenter: 강태원 · Keywords: #Anomaly Detection #Autoencoder #Causality #UnsupervisedLearning

Paper Review Multi-View Integrative Attention-Based Deep Representation Learning for Irregular Clinical Time-Series Data (2022)

Presenter: Hyejin Cho · Keywords: #Irregular time series #Attention

Paper Review Learning with Imbalanced Noisy Data by Preventing Bias in Sample Selection (IEEE Trans. Multimed. 2024)

Presenter: Jae Hun Cho · Keywords: #classification #Noisy label learning #Sample selection #Class imbalance

Paper Review Precursor-of-anomaly detection for irregular time series (KDD, 2023)

Presenter: SeungSu Kam · Keywords: #Neural Differential Equation #Time-series anomaly detection

Paper Review Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels

Presenter: Seongjin · Keywords: #Noisy label learning

Paper Review Wind Turbine Gearbox Failure Detection Through Cumulative Sum of Multivariate Time Series Data (Front. Energy Res. 2022)

Presenter: 강태원 · Keywords: #Anomaly Detection #Time-series anomaly detection

Lab Seminar Machine Learning for Survival Analysis: A Survey (2019)

Presenter: Hyejin Cho · Keywords: #Survival Analysis

Paper Review QuantTree: Histograms for Change Detection in Multivariate Data Streams (ICML 2018)

Presenter: Jae Hun Cho · Keywords: #Change Detection

Paper Review Attention-based Representation Learning for Time Series with Principal and Residual Space Monitoring

Presenter: Seongjin · Keywords: #Anomaly Detection #Representation Learning #Attention #time series #residual space

Paper Review ITRANSFORMER: Inverted Transformers Are Effective for Time Series Forecasting (ICLR, 2024)

Presenter: SeungSu Kam · Keywords: #Transformer #time-series forecasting

Paper Review Deep Anomaly Detection with Outlier Exposure (ICLR 2019)

Presenter: 강태원 · Keywords: #Anomaly Detection #outlier exposure

Paper Review Active Domain Adaptation via Clustering Uncertainty-Weighted Embeddings (ICCV 2021)

Presenter: Byungkook Koo · Keywords: #Domain adaptation #Active learning

Paper Review ABC: Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning (NeurIPS 2021)

Presenter: Hyejin Cho · Keywords: #semi-supervised learning #Imbalanced Data #Decoupled Training

Paper Review Neural ordinary differential equations(NeurIPS 2018)

Presenter: SeungSu Kam · Keywords: #Neural Differential Equation

Paper Review Moderate Coreset: A Universal Method of Data Selection for Real-world Data-efficient Deep Learning (ICLR 2023)

Presenter: Jae Hun Cho · Keywords: #Coreset selection #Dataset pruning #DeepLearning

Paper Review Modeling Stochastic Variability in Multiband Time-series Data (AJ, 2020)

Presenter: SeungSu Kam · Keywords: #Irregular time series #Time Modeling

Paper Review Efficient Parameter-free Clustering Using First Neighbor Relations (CVPR 2019)

Presenter: Chanbeom · Keywords: #Clustering

Paper Review SAITS: Self-attention-based imputation for time series (ESWA 2023)

Presenter: Yongmin Kim · Keywords: #Irregular time series #Self-attention

Paper Review Towards Total Recall in Industrial Anomaly Detection (CVPR 2022)

Presenter: 강태원 · Keywords: #Anomaly Detection

Paper Review DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection (KDD 2023)

Presenter: Hyejin Cho · Keywords: #Time-series anomaly detection #Attention #Contrastive learning

Paper Review Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization (NeurIPS 2020)

Presenter: Jae Hun Cho · Keywords: #DeepLearning #Domain Generalization #Medical Imaging

Paper Review Calibrating Histopathology Image Classifiers Using Label Smoothing (AIME 2022)

Presenter: Byungkook Koo · Keywords: #Label Smoothing #Model Calibration

Paper Review Neural Controlled Differential Equations for Online Prediction Tasks (2022)

Presenter: SeungSu Kam · Keywords: #Neural Differential Equation #Online Prediction

Lab Seminar Introduction to Gaussian Mixture Model(GMM) & EM Algorithm

Presenter: Hyejin Cho · Keywords: #Gaussian Mixture Model #EM Algorithm #UnsupervisedLearning

Paper Review Deep-CSA: Deep Contrastive Learning for Dynamic Survival Analysis With Competing Risks (JBHI 2022)

Presenter: Jae Hun Cho · Keywords: #Survival Analysis #Contrastive learning #DeepLearning

Paper Review SWAD: Domain Generalization by Seeking Flat Minima (NeurIPS 2021)

Presenter: Byungkook Koo · Keywords: #Domain Generalization #optimization

Paper Review SurvLatent ODE: A Neural ODE based time-to-event model with competing risks for longitudinal data improves cancer-associated Venous Thromboembolism (VTE) prediction (PMLR, 2022)

Presenter: SeungSu Kam · Keywords: #Survival Analysis #Neural Differential Equation

Paper Review Neural Flows: Efficient Alternative to Neural ODEs (NeurIPS 2021)

Presenter: YongKyung Oh · Keywords: #Neural Differential Equation #Flow

Paper Review Loyalty Formation for Different Customer Journey Segments (2019)

Presenter: Hyejin Cho · Keywords: #Latent Class Analysis #UnsupervisedLearning

Paper Review POEM: Polarization of Embeddings for Domain-Invariant Representations (AAAI 2023)

Presenter: Jae Hun Cho · Keywords: #Domain Generalization

Paper Review Bidirectional Learning for Domain Adaptation of Semantic Segmentation (CVPR 2019)

Presenter: Byungkook Koo · Keywords: #Domain adaptation #Bidirectional learning

Paper Review Attention Bottlenecks for Multimodal Fusion (NeurIPS 2021)

Presenter: Hyejin Cho · Keywords: #multi-modal learning #Transformer

Paper Review DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network (ICML WCB 2016)

Presenter: Jae Hun Cho

Paper Review (Neural Comput & Applic 2021) One-class graph neural networks for anomaly detection in attributed networks

Presenter: Ji In Kwak · Keywords: #Graph Anomaly Detection #UnsupervisedLearning #One-class classification

Lab Seminar A Simple Framework for Contrastive Learning of Visual Representations (ICML 2020)

Presenter: 유지태 · Keywords: #Contrastive learning #visual representation #Self-supervised Learning

Paper Review High-Resolution Image Synthesis With Latent Diffusion Models (CVPR 2022)

Presenter: Byungkook Koo · Keywords: #Diffusion Model #Text-to-Image #Generative Model

Paper Review Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness (NeurIPS 2020)

Presenter: SeungSu Kam · Keywords: #DeepLearning #Uncertainty Estimation

Paper Review Unsupervised Label Noise Modeling and Loss Correction (ICML 2019)

Presenter: YongKyung Oh · Keywords: #Noisy label learning

Paper Review EXPLAINABLE DEEP ONE-CLASS CLASSIFICATION (ICLR 2021)

Presenter: 유지태 · Keywords: #outlier exposure #Anomaly Detection #XAI

Paper Review Transfusion: Understanding Transfer Learning for Medical Imaging (NeurIPS 2019)

Presenter: Byungkook Koo · Keywords: #Medical Imaging #Transfer Learning #XAI

Paper Review Deep Semi-Supervised Anomaly Detection (ICLR 2020)

Presenter: SeungSu Kam · Keywords: #Anomaly Detection #semi-supervised learning

Paper Review Image Style Transfer Using Convolutional Neural Networks (CVPR 2016)

Presenter: Byungkook Koo · Keywords: #Style Transfer #CNN #Image Representation

Paper Review Constructing a Control Chart Using Functional Data (Mathematics 2020)

Presenter: SeungSu Kam · Keywords: #Functional Data #Functional depth #ControlChart

Lab Seminar Conditional score-based diffusion models for probabilistic time series imputation (NeurIPS 2021)

Presenter: YongKyung Oh · Keywords: #Generative Model #Diffusion Model

Paper Review SwinIR: Image Restoration Using Swin Transformer (ICCVW 2021)

Presenter: Byungkook Koo · Keywords: #Image Super Resolution #Swin Transformer #Image Restoration #Vision Transformer

Paper Review End-to-end unsupervised fault detection using a flow based model (RESS 2021)

Presenter: SeungSu Kam · Keywords: #Normalizing Flow

Paper Review Latent ODE + ODE-GRU/ ODE-LSTM (NeurIPS 2019)

Presenter: · Keywords: #Neural Differential Equation