News 2023
Paper Release: Improving Efficiency of Diffusion Models via Multi-Stage Framework and Tailored Multi-Decoder Architectures (Dec. 2023)
Invited talk : Systems | Information | Learning | Optimization (SILO) Seminar , UW Madison (Dec. 6th)
CAMSAP’23 Special Session: Learning and Optimization for Computational Imaging (Dec. 2023)
Award: Our paper The Emergence of Reproducibility and Consistency in Diffusion Models , has been recognized by the Best Paper Award at NeurIPS Diffusion Model Workshop 2023 (Nov. 2023)
Paper Release: Efficient Compression of Overparameterized Deep Models through Low-Dimensional Learning Dynamics (Nov. 2023)
Paper Release: Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination (Nov. 2023)
Invited talk : Columbia University, EE Department Seminar (Nov. 10th)
Invited talk : Machine Learning Seminar at the University of Pennsylvania (Nov. 17th)
Invited talk: DSI Machine Learning Seminar , University of Minnesota (Nov. 7th)
Invited talk: Math and Data (MAD) Seminar at New York University (Nov. 9th)
Student Award: My postdoc Peng Wang received a Rising Star Award at CPAL’24 (Oct. 2023)
Paper Release: Neural Collapse in Multi-label Learning with Pick-all-label Loss (Oct. 2023)
Paper Release: The Emergence of Reproducibility and Consistency in Diffusion Models , short version selected as an oral (top 2%) at NeurIPS 2023 Workshop on Diffusion Models (Oct. 2023)
Paper Release: Generalized Neural Collapse for a Large Number of Classes (Oct. 2023)
Grant approval: Received a MICDE Catalyst Grant on Efficient Diffusion Models for Scientific Machine Learning , joint with Prof. Liyue Shen and Prof. Jeff Fessler . (Oct. 2023)
Paper Release: Investigating the Catastrophic Forgetting in Multimodal Large Language Models (Sept. 2023)
Paper Release: Diffusion-based Adversarial Purification for Robust Deep MRI Reconstruction (Sept. 2023)
Talk: Presentation at Allerton Conference (Sept. 2023)
Public service: Invited to be an Area Chair of ICLR’24 (Sept. 2023)
Public Service: Symposium at MIDAS: Generative AI: Diffusion Models for Scientific Machine Learning (Sept. 15th, 2023)
Talk: Presentation at UM CSP Seminar, slides , video (Sept. 2023)
Public service: Invited to be an Area Chair of ICLR’24 (Aug. 2023)
Paper release: Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency (Jul. 2023)
Grant approval: Received a new three-year NSF RI medium grant in collaboration with Prof. Zhihui Zhu (OSU) and Prof. Jeremias Sulam (JHU), for supporting our research on deep representation learning via neural collapse (Jun. 2023).
Paper release: The Law of Parsimony in Gradient Descent for Learning Deep Linear Networks (Jun. 2023)
Outreach: Gave four lectures at 6th Advanced Course on Data Science & Machine Learning (ACDL‘23) (Jun. 2023)
Outreach: Gave an educational course at ICASSP’23: Learning Nonlinear and Deep Low-Dimensional Representations from High-Dimensional Data: From Theory to Practice (Jun. 2023)
Public service: Invited to be an Area Chair of NeurIPS’23 (Apr. 2023)
Grant approval: received a gift grant from Amazon Research Awards . (Mar. 2023)
Public service: Organized and gave a talk at the 3rd SLowDNN Workshop from Jan. 3rd to 6th at MBZUAI, Abu Dhabi, MBZUAI. (Jan. 2023)