Jaesik Choi - RankMe

164 papers A* 42A 13B 3Journal 79Unranked 26

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	An Empirical Study on Knowledge Transfer under Domain and Label Shifts in 3D LiDAR Point Clouds. CoRR SuBeen Lee, Siyeong Lee, Namil Kim, Jaesik Choi
2026	J	`jnl`	Towards Transparent Time Series Analysis: Exploring Methods and Enhancing Interpretability. ACM Comput. Surv. Youngjin Park, Anh Tong, Sehyun Lee, Jihyeon Seong, Qin Xie, Jaesik Choi
2025	A	`conf`	Amortized Baseline Selection via Rank-Revealing QR for Efficient Model Explanation. CIKM Chanwoo Lee, Youngjin Park, Hyeongeun Lee, Yeeun Yoo, Daehee Han, Junho Choi, Geonhyeong Kim, Nari Kim, Jaesik Choi
2025	J	`jnl`	Conditional Temporal Neural Processes with Covariance Loss. CoRR Boseon Yoo, Jiwoo Lee, Janghoon Ju, Seijun Chung, Soyeon Kim, Jaesik Choi
2025	J	`jnl`	Context-Aware Negative Sampling for Sequential Recommendation. IEEE Access Jinseok Seol, Jaesik Choi
2025	A	`conf`	Counterfactual Activation Editing for Post-hoc Prosody and Mispronunciation Correction in TTS Models. INTERSPEECH Kyowoon Lee, Artyom Stitsyuk, Gunu Jho, Inchul Hwang, Jaesik Choi
2025	J	`jnl`	Counterfactual Activation Editing for Post-hoc Prosody and Mispronunciation Correction in TTS Models. CoRR Kyowoon Lee, Artyom Stitsyuk, Gunu Jho, Inchul Hwang, Jaesik Choi
2025	J	`jnl`	Deep-DFVAR: Dynamic factor vector autoregression with deep learning for regional house price index forecasting. Neurocomputing Jisu Yeo, Artyom Stitsyuk, Jaesik Choi
2025	—	`conf`	Deontological Keyword Bias: The Impact of Modal Expressions on Normative Judgments of Language Models. ACL (1) Bumjin Park, Leejinsil Leejinsil, Jaesik Choi
2025	J	`jnl`	Deontological Keyword Bias: The Impact of Modal Expressions on Normative Judgments of Language Models. CoRR Bumjin Park, Jinsil Lee, Jaesik Choi
2025	A*	`conf`	Diverse Rare Sample Generation with Pretrained GANs. AAAI SuBeen Lee, Jiyeon Han, Soyeon Kim, Jaesik Choi
2025	A*	`conf`	Enhancing Creative Generation on Stable Diffusion-based Models. CVPR Jiyeon Han, Dahee Kwon, Gayoung Lee, Junho Kim, Jaesik Choi
2025	J	`jnl`	Enhancing Creative Generation on Stable Diffusion-based Models. CoRR Jiyeon Han, Dahee Kwon, Gayoung Lee, Junho Kim, Jaesik Choi
2025	J	`jnl`	Example-Based Concept Analysis Framework for Deep Weather Forecast Models. CoRR Soyeon Kim, Junho Choi, SuBeen Lee, Jaesik Choi
2025	J	`jnl`	Explainable AI-Based Interface System for Weather Forecasting Model. CoRR Soyeon Kim, Junho Choi, Yeji Choi, SuBeen Lee, Artyom Stitsyuk, Minkyoung Park, Seongyeop Jeong, Youhyun Baek, Jaesik Choi
2025	J	`jnl`	Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations. CoRR Dahee Kwon, Sehyun Lee, Jaesik Choi
2025	A	`conf`	Human-Centric AI: From Explainability and Trustworthiness to Actionable Ethics. CIKM Jaesik Choi, Bohyung Han, Myoung-Wan Koo, Kyungman Bae, Chang D. Yoo, Simon S. Woo, Wojciech Samek
2025	A*	`conf`	Local Manifold Approximation and Projection for Manifold-Aware Diffusion Planning. ICML Kyowoon Lee, Jaesik Choi
2025	J	`jnl`	Local Manifold Approximation and Projection for Manifold-Aware Diffusion Planning. CoRR Kyowoon Lee, Jaesik Choi
2025	J	`jnl`	Low-rank perturbation adjustment (LoPA): An implicit regularization method in image classification. Multim. Tools Appl. Nesma Talaat Abbas Mahmoud, Hanna Antson, Wai Tik Chan, Modar Sulaiman, Jaesik Choi, Osamu Shimmi, Kallol Roy
2025	A*	`conf`	Neural ODE Transformers: Analyzing Internal Dynamics and Adaptive Fine-tuning. ICLR Anh Tong, Thanh Nguyen-Tang, Dongeun Lee, Duc Nguyen, Toan M. Tran, David Leo Wright Hall, Cheongwoong Kang, Jaesik Choi
2025	J	`jnl`	Neural ODE Transformers: Analyzing Internal Dynamics and Adaptive Fine-tuning. CoRR Anh Tong, Thanh Nguyen-Tang, Dongeun Lee, Duc Nguyen, Toan M. Tran, David Hall, Cheongwoong Kang, Jaesik Choi
2025	A*	`conf`	On the Relationship Between Populated Regions and Adversarial Robustness in Deep Neural Networks. ICDM Seongjin Park, Haedong Jeong, Tair Djanibekov, Giyoung Jeon, Jinseok Seol, Jaesik Choi
2025	J	`jnl`	Pathwise Explanation of ReLU Neural Networks. CoRR Seongwoo Lim, Won Jo, Joohyung Lee, Jaesik Choi
2025	J	`jnl`	PnPXAI: A Universal XAI Framework Providing Automatic Explanations Across Diverse Modalities and Models. CoRR Seongun Kim, Sol A Kim, Geonhyeong Kim, Enver Menadjiev, Chanwoo Lee, Seongwook Chung, Nari Kim, Jaesik Choi
2025	J	`jnl`	Probing Network Decisions: Capturing Uncertainties and Unveiling Vulnerabilities Without Label Information. CoRR Youngju Joung, Sehyun Lee, Jaesik Choi
2025	A*	`conf`	Rethinking Shapley Value for Negative Interactions in Non-convex Games. ICLR Wonjoon Chang, Myeongjin Lee, Jaesik Choi
2025	J	`jnl`	State-Covering Trajectory Stitching for Diffusion Planners. CoRR Kyowoon Lee, Jaesik Choi
2025	—	`conf`	When Format Changes Meaning: Investigating Semantic Inconsistency of Large Language Models. EMNLP (Findings) Cheongwoong Kang, Jongeun Baek, Yeonjea Kim, Jaesik Choi
2025	A*	`conf`	xPatch: Dual-Stream Time Series Forecasting with Exponential Seasonal-Trend Decomposition. AAAI Artyom Stitsyuk, Jaesik Choi
2024	J	`jnl`	Capsule Neural Networks as Noise Stabilizer for Time Series Data. CoRR Soyeon Kim, Jihyeon Seong, Hyunkyung Han, Jaesik Choi
2024	—	`conf`	CardioCaps: Attention-Based Capsule Network for Class-Imbalanced Echocardiogram Classification. BigComp Hyunkyung Han, Jihyeon Seong, Jaesik Choi
2024	J	`jnl`	CardioCaps: Attention-based Capsule Network for Class-Imbalanced Echocardiogram Classification. CoRR Hyunkyung Han, Jihyeon Seong, Jaesik Choi
2024	J	`jnl`	Diverse Rare Sample Generation with Pretrained GANs. CoRR SuBeen Lee, Jiyeon Han, Soyeon Kim, Jaesik Choi
2024	J	`jnl`	Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions. Inf. Fusion Luca Longo, Mario Brcic, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lécué, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Timo Speith, Simone Stumpf
2024	—	`conf`	Identifying the Source of Generation for Large Language Models. ICPRAI (2) Bumjin Park, Jaesik Choi
2024	J	`jnl`	Identifying the Source of Generation for Large Language Models. CoRR Bumjin Park, Jaesik Choi
2024	A*	`conf`	Memorizing Documents with Guidance in Large Language Models. IJCAI Bumjin Park, Jaesik Choi
2024	J	`jnl`	Memorizing Documents with Guidance in Large Language Models. CoRR Bumjin Park, Jaesik Choi
2024	J	`jnl`	Optimal path for Biomedical Text Summarization Using Pointer GPT. CoRR Hyunkyung Han, Jaesik Choi
2024	A	`conf`	Pathwise Explanation of ReLU Neural Networks. AISTATS Seongwoo Lim, Won Jo, Joohyung Lee, Jaesik Choi
2024	—	`conf`	Probing Network Decisions: Capturing Uncertainties and Unveiling Vulnerabilities Without Label Information. ICPRAI (1) Youngju Joung, Sehyun Lee, Jaesik Choi
2024	A*	`conf`	Towards Diverse Perspective Learning with Selection over Multiple Temporal Poolings. AAAI Jihyeon Seong, Jungmin Kim, Jaesik Choi
2024	J	`jnl`	Towards Diverse Perspective Learning with Selection over Multiple Temporal Poolings. CoRR Jihyeon Seong, Jungmin Kim, Jaesik Choi
2024	A*	`conf`	Towards Dynamic Trend Filtering through Trend Point Detection with Reinforcement Learning. IJCAI Jihyeon Seong, Sekwang Oh, Jaesik Choi
2024	J	`jnl`	Towards Dynamic Trend Filtering through Trend Point Detection with Reinforcement Learning. CoRR Jihyeon Seong, Sekwang Oh, Jaesik Choi
2024	A*	`conf`	Understanding Distributed Representations of Concepts in Deep Neural Networks without Supervision. AAAI Wonjoon Chang, Dahee Kwon, Jaesik Choi
2024	J	`jnl`	xPatch: Dual-Stream Time Series Forecasting with Exponential Seasonal-Trend Decomposition. CoRR Artyom Stitsyuk, Jaesik Choi
2023	A*	`conf`	Adaptive and Explainable Deployment of Navigation Skills via Hierarchical Deep Reinforcement Learning. ICRA Kyowoon Lee, Seongun Kim, Jaesik Choi
2023	J	`jnl`	Adaptive and Explainable Deployment of Navigation Skills via Hierarchical Deep Reinforcement Learning. CoRR Kyowoon Lee, Seongun Kim, Jaesik Choi
2023	A	`conf`	Algorithmic Read Resistance Trim for Improving Yield and Reducing Test Time in MRAM. ITC Daehyun Chang, Youngdae Kim, Suksoo Pyo, Shin Hun, Daesop Lee, Sohee Hwang, Jaesik Choi, Siwoong Kim
2023	A*	`conf`	Beyond Single Path Integrated Gradients for Reliable Input Attribution via Randomized Path Sampling. ICCV Giyoung Jeon, Haedong Jeong, Jaesik Choi
2023	J	`jnl`	CR-COPEC: Causal Rationale of Corporate Performance Changes to Learn from Financial Reports. CoRR Ye Eun Chun, Sunjae Kwon, Kyunghwan Sohn, Nakwon Sung, Junyoup Lee, Byungki Seo, Kevin Compher, Seung-won Hwang, Jaesik Choi
2023	—	`conf`	CR-COPEC: Causal Rationale of Corporate Performance Changes to learn from Financial Reports. EMNLP (Findings) Ye Eun Chun, Sunjae Kwon, Kyunghwan Sohn, Nakwon Sung, Junyoup Lee, Byoung Seo, Kevin Compher, Seung-won Hwang, Jaesik Choi
2023	—	`conf`	Explainable AI-Based Interface System for Weather Forecasting Model. HCI (53) Soyeon Kim, Junho Choi, Yeji Choi, SuBeen Lee, Artyom Stitsyuk, Minkyoung Park, Seongyeop Jeong, You-Hyun Baek, Jaesik Choi
2023	J	`jnl`	Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions. CoRR Luca Longo, Mario Brcic, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lécué, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Timo Speith, Simone Stumpf
2023	J	`jnl`	Explaining the Decisions of Deep Policy Networks for Robotic Manipulations. CoRR Seongun Kim, Jaesik Choi
2023	—	`conf`	Impact of Co-occurrence on Factual Knowledge of Large Language Models. EMNLP (Findings) Cheongwoong Kang, Jaesik Choi
2023	J	`jnl`	Impact of Co-occurrence on Factual Knowledge of Large Language Models. CoRR Cheongwoong Kang, Jaesik Choi
2023	A*	`conf`	Rarity Score : A New Metric to Evaluate the Uncommonness of Synthesized Images. ICLR Jiyeon Han, Hwanil Choi, Yunjey Choi, Junho Kim, Jung-Woo Ha, Jaesik Choi
2023	A*	`conf`	Refining Diffusion Planner for Reliable Behavior Synthesis by Automatic Detection of Infeasible Plans. NeurIPS Kyowoon Lee, Seongun Kim, Jaesik Choi
2023	J	`jnl`	Refining Diffusion Planner for Reliable Behavior Synthesis by Automatic Detection of Infeasible Plans. CoRR Kyowoon Lee, Seongun Kim, Jaesik Choi
2023	—	`conf`	SigFormer: Signature Transformers for Deep Hedging. ICAIF Anh Tong, Thanh Nguyen-Tang, Dongeun Lee, Toan M. Tran, Jaesik Choi
2023	J	`jnl`	SigFormer: Signature Transformers for Deep Hedging. CoRR Anh Tong, Thanh Nguyen-Tang, Dongeun Lee, Toan M. Tran, Jaesik Choi
2023	J	`jnl`	Stress and Adaptation: Applying Anna Karenina Principle in Deep Learning for Image Classification. CoRR Nesma Mahmoud, Hanna Antson, Jaesik Choi, Osamu Shimmi, Kallol Roy
2023	J	`jnl`	The Disharmony Between BN and ReLU Causes Gradient Explosion, but is Offset by the Correlation Between Activations. CoRR Inyoung Paik, Jaesik Choi
2023	J	`jnl`	Understanding Distributed Representations of Concepts in Deep Neural Networks without Supervision. CoRR Wonjoon Chang, Dahee Kwon, Jaesik Choi
2023	A*	`conf`	Variational Curriculum Reinforcement Learning for Unsupervised Discovery of Skills. ICML Seongun Kim, Kyowoon Lee, Jaesik Choi
2023	J	`jnl`	Variational Curriculum Reinforcement Learning for Unsupervised Discovery of Skills. CoRR Seongun Kim, Kyowoon Lee, Jaesik Choi
2022	A*	`conf`	An Unsupervised Way to Understand Artifact Generating Internal Units in Generative Neural Networks. AAAI Haedong Jeong, Jiyeon Han, Jaesik Choi
2022	A*	`conf`	Can We Find Neurons that Cause Unrealistic Images in Deep Generative Networks? IJCAI Hwanil Choi, Wonjoon Chang, Jaesik Choi
2022	J	`jnl`	Can We Find Neurons that Cause Unrealistic Images in Deep Generative Networks? CoRR Hwanil Choi, Wonjoon Chang, Jaesik Choi
2022	A*	`conf`	Distilled Gradient Aggregation: Purify Features for Input Attribution in the Deep Neural Network. NeurIPS Giyoung Jeon, Haedong Jeong, Jaesik Choi
2022	J	`jnl`	Explanation on Pretraining Bias of Finetuned Vision Transformer. CoRR Bumjin Park, Jaesik Choi
2022	A*	`conf`	Learning Fractional White Noises in Neural Stochastic Differential Equations. NeurIPS Anh Tong, Thanh Nguyen-Tang, Toan M. Tran, Jaesik Choi
2022	J	`jnl`	On the Relationship Between Adversarial Robustness and Decision Region in Deep Neural Network. CoRR Seongjin Park, Haedong Jeong, Giyoung Jeon, Jaesik Choi
2022	J	`jnl`	Rarity Score : A New Metric to Evaluate the Uncommonness of Synthesized Images. CoRR Jiyeon Han, Hwanil Choi, Yunjey Choi, Junho Kim, Jung-Woo Ha, Jaesik Choi
2022	J	`jnl`	Scheduling PID Attitude and Position Control Frequencies for Time-Optimal Quadrotor Waypoint Tracking under Unknown External Disturbances. Sensors Cheongwoong Kang, Bumjin Park, Jaesik Choi
2022	J	`jnl`	Semisupervised Training of Deep Generative Models for High-Dimensional Anomaly Detection. IEEE Trans. Neural Networks Learn. Syst. Qin Xie, Peng Zhang, Boseon Yu, Jaesik Choi
2022	J	`jnl`	Variational Neural Temporal Point Process. CoRR Deokjun Eom, Sehyun Lee, Jaesik Choi
2022	J	`jnl`	Why Do Neural Language Models Still Need Commonsense Knowledge to Handle Semantic Variations in Question Answering? CoRR Sunjae Kwon, Cheongwoong Kang, Jiyeon Han, Jaesik Choi
2021	J	`jnl`	An Unsupervised Way to Understand Artifact Generating Internal Units in Generative Neural Networks. CoRR Haedong Jeong, Jiyeon Han, Jaesik Choi
2021	A*	`conf`	Automatic Correction of Internal Units in Generative Neural Networks. CVPR Ali Tousi, Haedong Jeong, Jiyeon Han, Hwanil Choi, Jaesik Choi
2021	J	`jnl`	Automatic Correction of Internal Units in Generative Neural Networks. CoRR Ali Tousi, Haedong Jeong, Jiyeon Han, Hwanil Choi, Jaesik Choi
2021	A*	`conf`	Characterizing Deep Gaussian Processes via Nonlinear Recurrence Systems. AAAI Anh Tong, Jaesik Choi
2021	A*	`conf`	Conditional Temporal Neural Processes with Covariance Loss. ICML Boseon Yoo, Jiwoo Lee, Janghoon Ju, Seijun Chung, Soyeon Kim, Jaesik Choi
2021	A	`conf`	Explaining the Decisions of Deep Policy Networks for Robotic Manipulations. IROS Seongun Kim, Jaesik Choi
2021	A*	`conf`	Interpreting Deep Neural Networks with Relative Sectional Propagation by Analyzing Comparative Gradients and Hostile Activations. AAAI Woo-Jeoung Nam, Jaesik Choi, Seong-Whan Lee
2021	A*	`conf`	Interpreting Internal Activation Patterns in Deep Temporal Neural Networks by Finding Prototypes. KDD Sohee Cho, Wonjoon Chang, Ginkyeng Lee, Jaesik Choi
2021	A*	`conf`	Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior. AAAI Anh Tong, Toan M. Tran, Hung Bui, Jaesik Choi
2020	A*	`conf`	A Single Multi-Task Deep Neural Network with Post-Processing for Object Detection with Reasoning and Robotic Grasp Detection. ICRA Dongwon Park, Yonghyeok Seo, Dongju Shin, Jaesik Choi, Se Young Chun
2020	A*	`conf`	An Efficient Explorative Sampling Considering the Generative Boundaries of Deep Generative Neural Networks. AAAI Giyoung Jeon, Haedong Jeong, Jaesik Choi
2020	J	`jnl`	Characterizing Deep Gaussian Processes via Nonlinear Recurrence Systems. CoRR Anh Tong, Jaesik Choi
2020	—	`conf`	HetPipe: Enabling Large DNN Training on (Whimpy) Heterogeneous GPU Clusters through Integration of Pipelined Model Parallelism and Data Parallelism. USENIX ATC Jay H. Park, Gyeongchan Yun, Chang M. Yi, Nguyen T. Nguyen, Seungmin Lee, Jaesik Choi, Sam H. Noh, Young-ri Choi
2020	J	`jnl`	HetPipe: Enabling Large DNN Training on (Whimpy) Heterogeneous GPU Clusters through Integration of Pipelined Model Parallelism and Data Parallelism. CoRR Jay H. Park, Gyeongchan Yun, Chang M. Yi, Nguyen T. Nguyen, Seungmin Lee, Jaesik Choi, Sam H. Noh, Young-ri Choi
2020	J	`jnl`	Improved Predictive Deep Temporal Neural Networks with Trend Filtering. CoRR Youngjin Park, Deokjun Eom, Byoungki Seo, Jaesik Choi
2020	—	`conf`	Improved predictive deep temporal neural networks with trend filtering. ICAIF Youngjin Park, Deokjun Eom, Byoungki Seo, Jaesik Choi
2020	J	`jnl`	Interpretation of Deep Temporal Representations by Selective Visualization of Internally Activated Units. CoRR Sohee Cho, Ginkyeng Lee, Jaesik Choi
2020	J	`jnl`	Interpreting Deep Neural Networks with Relative Sectional Propagation by Analyzing Comparative Gradients and Hostile Activations. CoRR Woo-Jeoung Nam, Jaesik Choi, Seong-Whan Lee
2020	A*	`conf`	Interpreting and Explaining Deep Neural Networks: A Perspective on Time Series Data. KDD Jaesik Choi
2020	J	`jnl`	Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior. CoRR Anh Tong, Toan M. Tran, Hung Bui, Jaesik Choi
2020	A*	`conf`	Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networks. AAAI Woo-Jeoung Nam, Shir Gur, Jaesik Choi, Lior Wolf, Seong-Whan Lee
2019	J	`jnl`	A Single Multi-Task Deep Neural Network with Post-Processing for Object Detection with Reasoning and Robotic Grasp Detection. CoRR Dongwon Park, Yonghyeok Seo, Dongju Shin, Jaesik Choi, Se Young Chun
2019	J	`jnl`	An Efficient Explorative Sampling Considering the Generative Boundaries of Deep Generative Neural Networks. CoRR Giyoung Jeon, Haedong Jeong, Jaesik Choi
2019	A*	`conf`	Confirmatory Bayesian Online Change Point Detection in the Covariance Structure of Gaussian Processes. IJCAI Jiyeon Han, Kyowoon Lee, Anh Tong, Jaesik Choi
2019	J	`jnl`	Confirmatory Bayesian Online Change Point Detection in the Covariance Structure of Gaussian Processes. CoRR Jiyeon Han, Kyowoon Lee, Anh Tong, Jaesik Choi
2019	A*	`conf`	Discovering Latent Covariance Structures for Multiple Time Series. ICML Anh Tong, Jaesik Choi
2019	J	`jnl`	IDEALEM: Statistical Similarity Based Data Reduction. CoRR Dongeun Lee, Alex Sim, Jaesik Choi, Kesheng Wu
2019	J	`jnl`	Markov Information Bottleneck to Improve Information Flow in Stochastic Neural Networks. Entropy Thanh T. Nguyen, Jaesik Choi
2019	J	`jnl`	Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networks. CoRR Woo-Jeoung Nam, Jaesik Choi, Seong-Whan Lee
2019	J	`jnl`	Why Do Masked Neural Language Models Still Need Common Sense Knowledge? CoRR Sunjae Kwon, Cheongwoong Kang, Jiyeon Han, Jaesik Choi
2019	J	`jnl`	XAI - Explainable artificial intelligence. Sci. Robotics David Gunning, Mark Stefik, Jaesik Choi, Timothy Miller, Simone Stumpf, Guang-Zhong Yang
2018	A*	`conf`	Deep Reinforcement Learning in Continuous Action Spaces: a Case Study in the Game of Simulated Curling. ICML Kyowoon Lee, Sol-A. Kim, Jaesik Choi, Seong-Whan Lee
2018	—	`conf`	Dynamic Online Performance Optimization in Streaming Data Compression. IEEE BigData J. Kade Gibson, Dongeun Lee, Jaesik Choi, Alex Sim
2018	—	`conf`	Learning the Group Structure of Deep Neural Networks with an Expectation Maximization Method. ICDM Workshops Subin Yi, Jaesik Choi
2018	J	`jnl`	Predicting baseline for analysis of electricity pricing. Int. J. Big Data Intell. Taehoon Kim, Jaesik Choi, Dongeun Lee, Alex Sim, C. Anna Spurlock, Annika Todd, Kesheng Wu
2017	J	`jnl`	Automatic Decomposition of Self-Triggering Kernels of Hawkes Processes. CoRR Rafael Lima, Jaesik Choi
2017	B	`conf`	Expanding Statistical Similarity Based Data Reduction to Capture Diverse Patterns. DCC Dongeun Lee, Alex Sim, Jaesik Choi, Kesheng Wu
2017	J	`jnl`	Grouped Convolutional Neural Networks for Multivariate Time Series. CoRR Subin Yi, Janghoon Ju, Man-Ki Yoon, Jaesik Choi
2017	B	`conf`	Improving Statistical Similarity Based Data Reduction for Non-Stationary Data. SSDBM Dongeun Lee, Alex Sim, Jaesik Choi, Kesheng Wu
2017	J	`jnl`	Layer-wise Learning of Stochastic Neural Networks with Information Bottleneck. CoRR Thanh T. Nguyen, Jaesik Choi
2017	—	`conf`	Learning Execution Contexts from System Call Distribution for Anomaly Detection in Smart Embedded System. IoTDI Man-Ki Yoon, Sibin Mohan, Jaesik Choi, Mihai Christodorescu, Lui Sha
2017	—	`conf`	UNIST SAIL System for TAC 2017 Cold Start Slot Filling. TAC Seongwoo Lim, Soonjae Kwon, Sehyun Lee, Jaesik Choi
2016	J	`jnl`	A Robot Learning to Play a Mobile Game Under Unknown Dynamics. CoRR Wonjun Yoon, Sol-A. Kim, Jaesik Choi
2016	A*	`conf`	Automatic Construction of Nonparametric Relational Regression Models for Multiple Time Series. ICML Yunseong Hwang, Anh Tong, Jaesik Choi
2016	A	`conf`	Global Deconvolutional Networks for Semantic Segmentation. BMVC Vladimir Nekrasov, Janghoon Ju, Jaesik Choi
2016	J	`jnl`	Global Deconvolutional Networks for Semantic Segmentation. CoRR Vladimir Nekrasov, Janghoon Ju, Jaesik Choi
2016	A	`conf`	Improving Imprecise Compressive Sensing Models. UAI Dongeun Lee, Rafael Lima, Jaesik Choi
2016	B	`conf`	Novel Data Reduction Based on Statistical Similarity. SSDBM Dongeun Lee, Alex Sim, Jaesik Choi, Kesheng Wu
2016	—	`conf`	SAIL (UNIST) team Participation in KBP 2016 Cold-Start Slot filling. TAC Seongwoo Lim, Jiyeon Han, Kyowoon Lee, Jaesik Choi
2016	J	`jnl`	Searching for Topological Symmetry in Data Haystack. CoRR Kallol Roy, Anh Tong, Jaesik Choi
2015	A*	`conf`	A Deterministic Partition Function Approximation for Exponential Random Graph Models. IJCAI Wen Pu, Jaesik Choi, Yunseong Hwang, Eyal Amir
2015	—	`conf`	Extracting Baseline Electricity Usage Using Gradient Tree Boosting. SmartCity Taehoon Kim, Dongeun Lee, Jaesik Choi, Anna Spurlock, Alex Sim, Annika Todd, Kesheng Wu
2015	J	`jnl`	Intrusion Detection Using Execution Contexts Learned from System Call Distributions of Real-Time Embedded Systems. CoRR Man-Ki Yoon, Sibin Mohan, Jaesik Choi, Mihai Christodorescu, Lui Sha
2015	A	`conf`	Learning Compressive Sensing Models for Big Spatio-Temporal Data. SDM Dongeun Lee, Jaesik Choi
2015	J	`jnl`	Learning Dynamic Compressive Sensing Models. CoRR Dongeun Lee, Jaesik Choi
2015	A*	`conf`	Learning Relational Kalman Filtering. AAAI Jaesik Choi, Eyal Amir, Tianfang Xu, Albert J. Valocchi
2015	A*	`conf`	Memory heat map: anomaly detection in real-time embedded systems using memory behavior. DAC Man-Ki Yoon, Lui Sha, Sibin Mohan, Jaesik Choi
2015	A*	`conf`	Reading Documents for Bayesian Online Change Point Detection. EMNLP Taehoon Kim, Jaesik Choi
2015	J	`jnl`	Semi-Local Structure Patterns for Robust Face Detection. IEEE Signal Process. Lett. Kyungjoong Jeong, Jaesik Choi, Gil-Jin Jang
2015	J	`jnl`	The Automatic Statistician: A Relational Perspective. CoRR Yunseong Hwang, Jaesik Choi
2014	—	`conf`	Low complexity sensing for big spatio-temporal data. IEEE BigData Dongeun Lee, Jaesik Choi
2014	J	`jnl`	Low-complexity compressive sensing with downsampling. IEICE Electron. Express Dongeun Lee, Jaesik Choi, Heonshik Shin
2014	—	`conf`	Parameter Estimation for Relational Kalman Filtering. StarAI@AAAI Jaesik Choi, Eyal Amir, Tianfang Xu, Albert J. Valocchi
2013	J	`jnl`	A spatio-temporal pyramid matching for video retrieval. Comput. Vis. Image Underst. Jaesik Choi, Ziyu Wang, Sang-Chul Lee, Won J. Jeon
2013	—	`conf`	Fast Change Point Detection for electricity market analysis. IEEE BigData William Gu, Jaesik Choi, Ming Gu, Horst D. Simon, Kesheng Wu
2013	—	`conf`	Lifted Inference on Transitive Relations. StarAI@AAAI Wen Pu, Jaesik Choi, Eyal Amir
2013	A	`conf`	SecureCore: A multicore-based intrusion detection architecture for real-time embedded systems. IEEE Real-Time and Embedded Technology and Applications Symposium Man-Ki Yoon, Sibin Mohan, Jaesik Choi, Jung-Eun Kim, Lui Sha
2012	J	`jnl`	Lifted Inference for Relational Continuous Models CoRR Jaesik Choi, Eyal Amir, David J. Hill
2012	—	`—`	Lifted Inference for Relational Hybrid Models Jaesik Choi
2012	J	`jnl`	Lifted Relational Variational Inference CoRR Jaesik Choi, Eyal Amir
2012	A	`conf`	Lifted Relational Variational Inference. UAI Jaesik Choi, Eyal Amir
2012	—	`conf`	Nonparametric Relational Hybrid Models. StarAI@UAI Jaesik Choi, Eyal Amir
2011	A*	`conf`	Efficient Methods for Lifted Inference with Aggregate Factors. AAAI Jaesik Choi, Rodrigo de Salvo Braz, Hung Hai Bui
2011	A*	`conf`	Lifted Relational Kalman Filtering. IJCAI Jaesik Choi, Abner Guzmán-Rivera, Eyal Amir
2010	—	`conf`	Combining Planning and Motion Planning. Cognitive Robotics Jaesik Choi, Eyal Amir
2010	—	`conf`	Lifted Inference for Relational Continuous Models. StarAI@AAAI Jaesik Choi, David J. Hill, Eyal Amir
2010	A	`conf`	Lifted Inference for Relational Continuous Models. UAI Jaesik Choi, Eyal Amir, David J. Hill
2009	A*	`conf`	Combining planning and motion planning. ICRA Jaesik Choi, Eyal Amir
2009	A*	`conf`	Greedy Algorithms for Sequential Sensing Decisions. IJCAI Hannaneh Hajishirzi, Afsaneh Shirazi, Jaesik Choi, Eyal Amir
2009	J	`jnl`	Safe Navigation of a Mobile Robot Considering Visibility of Environment. IEEE Trans. Ind. Electron. Woojin Chung, Seokgyu Kim, Minki Choi, Jaesik Choi, Hoyeon Kim, Chang-Bae Moon, Jae-Bok Song
2008	—	`conf`	Spatio-temporal pyramid matching for sports videos. Multimedia Information Retrieval Jaesik Choi, Won J. Jeon, Sang-Chul Lee
2007	A	`conf`	Factor-guided motion planning for a robot arm. IROS Jaesik Choi, Eyal Amir
2006	—	`conf`	Factored Planning for Controlling a Robotic Arm. AAAI Fall Symposium: Integrating Reasoning into Everyday Applications Jaesik Choi, Eyal Amir