[{'Paper': 'Robust Neural Rendering in the Wild with Asymmetric Dual 3D Gaussian Splatting', 'Conference': 'NeurIPS 2025', 'Type': 'spotlight (top ~3%)'}, {'Paper': 'Learning with Noisy Ground Truth: From 2D Classification to 3D Reconstruction', 'Platform': 'arxiv.org', 'Year': '2024'}, {'Paper': 'VastGaussian: Vast Gaussian for Large Scene Reconstruction', 'Conference': 'CVPR 2024', 'Year': '2024'}, {'Paper': 'Rethinking Label Refurbishment: Model Robustness under Label Noise', 'Conference': 'AAAI 2023', 'Year': '2023'}, {'Paper': 'Robust Approaches for Learning with Noisy Labels', 'Type': 'Ph.D. Thesis', 'Year': '2022'}, {'Paper': 'Noise Attention Learning', 'Conference': 'NeurIPS 2022', 'Year': '2022'}, {'Paper': 'SELC: Self-Ensemble Label Correction Improves Learning with Noisy Labels', 'Conference': 'IJCAI 2022', 'Type': 'regular paper', 'Year': '2022'}, {'Paper': 'An Ensemble Model for Combating Label Noise', 'Conference': 'WSDM 2022', 'Type': 'regular paper', 'Year': '2021'}, {'Paper': 'Confidence Adaptive Regularization for Deep Learning with Noisy Labels', 'Platform': 'arxiv.org', 'Year': '2021'}, {'Paper': 'CLTA: Contents and Length-based Temporal Attention for Few-shot Action Recognition', 'Platform': 'arxiv.org', 'Year': '2021'}]
Background
Current research interests broadly include theory and applications of machine learning, such as trustworthy machine learning, 3D reconstruction and generation, approximate nearest neighbor search, image and video classification.
Miscellany
Served as a reviewer for ICML 2022, NeurIPS 2022, AAAI 2023, AAAI 2024, and IEEE Transactions on Neural Networks and Learning Systems 2023.