Self-Training Of Graph Neural Networks Using Similarity Reference For Robust Training With Noisy Labels. - Hyoungseob Park; Minki Jeong; Youngeun Kim; Changick Kim (ICIP, 2020)

Domain Adaptation without Source Data. - Youngeun Kim; Sungeun Hong; Donghyeon Cho; Hyoungseob Park; Priyadarshini Panda (CoRR, 2020)

Meta Batch-Instance Normalization for Generalizable Person Re-Identification. - Seokeon Choi; Taekyung Kim 002; Minki Jeong; Hyoungseob Park; Changick Kim (CVPR, 2021)

Neural Architecture Search for Spiking Neural Networks. - Youngeun Kim; Yuhang Li 001; Hyoungseob Park; Yeshwanth Venkatesha; Priyadarshini Panda (ECCV (24), 2022)

Exploring Lottery Ticket Hypothesis in Spiking Neural Networks. - Youngeun Kim; Yuhang Li 001; Hyoungseob Park; Yeshwanth Venkatesha; Ruokai Yin; Priyadarshini Panda (ECCV (12), 2022)

Neuromorphic Data Augmentation for Training Spiking Neural Networks. - Yuhang Li 001; Youngeun Kim; Hyoungseob Park; Tamar Geller; Priyadarshini Panda (ECCV (7), 2022)

Rate Coding Or Direct Coding: Which One Is Better For Accurate, Robust, And Energy-Efficient Spiking Neural Networks? - Youngeun Kim; Hyoungseob Park; Abhishek Moitra; Abhiroop Bhattacharjee; Yeshwanth Venkatesha; Priyadarshini Panda (ICASSP, 2022)

Addressing Client Drift in Federated Continual Learning with Adaptive Optimization. - Yeshwanth Venkatesha; Youngeun Kim; Hyoungseob Park; Yuhang Li 001; Priyadarshini Panda (CoRR, 2022)

Wearable-based Human Activity Recognition with Spatio-Temporal Spiking Neural Networks. - Yuhang Li 001; Ruokai Yin; Hyoungseob Park; Youngeun Kim; Priyadarshini Panda (CoRR, 2022)

Robust Federated Learning With Noisy Labels. - Seunghan Yang; Hyoungseob Park; Junyoung Byun; Changick Kim (IEEE Intell. Syst., 2022)

Exploring Temporal Information Dynamics in Spiking Neural Networks. - Youngeun Kim; Yuhang Li 001; Hyoungseob Park; Yeshwanth Venkatesha; Anna Hambitzer; Priyadarshini Panda (AAAI, 2023)

AugUndo: Scaling Up Augmentations for Unsupervised Depth Completion. - Yangchao Wu; Tian Yu Liu; Hyoungseob Park; Stefano Soatto; Dong Lao; Alex Wong 001 (CoRR, 2023)

Uncovering the Representation of Spiking Neural Networks Trained with Surrogate Gradient. - Yuhang Li 001; Youngeun Kim; Hyoungseob Park; Priyadarshini Panda (Trans. Mach. Learn. Res., 2023)

Divide-and-conquer the NAS puzzle in resource-constrained federated learning systems. - Yeshwanth Venkatesha; Youngeun Kim; Hyoungseob Park; Priyadarshini Panda (Neural Networks, 2023)

Test- Time Adaptation for Depth Completion. - Hyoungseob Park; Anjali Gupta; Alex Wong 001 (CVPR, 2024)

Binding Touch to Everything: Learning Unified Multimodal Tactile Representations. - Fengyu Yang; Chao Feng; Ziyang Chen; Hyoungseob Park; Daniel Wang 005; Yiming Dou; Ziyao Zeng; Xien Chen; Rit Gangopadhyay; Andrew Owens; Alex Wong 001 (CVPR, 2024)

WorDepth: Variational Language Prior for Monocular Depth Estimation. - Ziyao Zeng; Daniel Wang 005; Fengyu Yang; Hyoungseob Park; Stefano Soatto; Dong Lao; Alex Wong 001 (CVPR, 2024)

On the Viability of Monocular Depth Pre-training for Semantic Segmentation. - Dong Lao; Fengyu Yang; Daniel Wang 005; Hyoungseob Park; Samuel Lu; Alex Wong 001; Stefano Soatto (ECCV (37), 2024)

AugUndo: Scaling Up Augmentations for Monocular Depth Completion and Estimation. - Yangchao Wu; Tian Yu Liu; Hyoungseob Park; Stefano Soatto; Dong Lao; Alex Wong 001 (ECCV (64), 2024)

All-day Depth Completion. - Vadim Ezhov; Hyoungseob Park; Zhaoyang Zhang; Rishi Upadhyay; Howard Zhang; Chethan Chinder Chandrappa; Achuta Kadambi; Yunhao Ba; Julie Dorsey; Alex Wong 001 (IROS, 2024)

RSA: Resolving Scale Ambiguities in Monocular Depth Estimators through Language Descriptions. - Ziyao Zeng; Yangchao Wu; Hyoungseob Park; Daniel Wang 005; Fengyu Yang; Stefano Soatto; Dong Lao; Byung-Woo Hong; Alex Wong 001 (NeurIPS, 2024)

WorDepth: Variational Language Prior for Monocular Depth Estimation. - Ziyao Zeng; Daniel Wang 005; Fengyu Yang; Hyoungseob Park; Yangchao Wu; Stefano Soatto; Byung-Woo Hong; Dong Lao; Alex Wong 001 (CoRR, 2024)

NeuroBind: Towards Unified Multimodal Representations for Neural Signals. - Fengyu Yang; Chao Feng; Daniel Wang 005; Tianye Wang; Ziyao Zeng; Zhiyang Xu; Hyoungseob Park; Pengliang Ji; Hanbin Zhao; Yuanning Li; Alex Wong 001 (CoRR, 2024)

UnCLe: Unsupervised Continual Learning of Depth Completion. - Suchisrit Gangopadhyay; Xien Chen; Michael Chu; Patrick Rim; Hyoungseob Park; Alex Wong 001 (CoRR, 2024)

TREND: Unsupervised 3D Representation Learning via Temporal Forecasting for LiDAR Perception. - Runjian Chen; Hyoungseob Park; Bo Zhang 069; Wenqi Shao; Ping Luo 002; Alex Wong 001 (CoRR, 2024)

ProtoDepth: Unsupervised Continual Depth Completion with Prototypes. - Patrick Rim; Hyoungseob Park; Suchisrit Gangopadhyay; Ziyao Zeng; Younjoon Chung; Alex Wong 001 (CVPR, 2025)

Progressive Test Time Energy Adaptation for Medical Image Segmentation. - Xiaoran Zhang; Byung-Woo Hong; Hyoungseob Park; Daniel H. Pak; Anne-Marie Rickmann; Lawrence H. Staib; James S. Duncan; Alex Wong 001 (CoRR, 2025)

Radar-Guided Polynomial Fitting for Metric Depth Estimation. - Patrick Rim; Hyoungseob Park; Vadim Ezhov; Jeffrey Moon; Alex Wong 001 (CoRR, 2025)

Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens. - Suchisrit Gangopadhyay; Jung-Hee Kim; Xien Chen; Patrick Rim; Hyoungseob Park; Alex Wong 001 (CoRR, 2025)

ETA: Energy-based Test-time Adaptation for Depth Completion. - Younjoon Chung; Hyoungseob Park; Patrick Rim; Xiaoran Zhang; Jihe He; Ziyao Zeng; Safa Cicek; Byung-Woo Hong; James S. Duncan; Alex Wong 001 (CoRR, 2025)