MLSP-L4.2
Neural Stochastic Differential Equations with Change Points: A Generative Adversarial Approach
Zhongchang Sun, University at Buffalo, the State University of New York, United States of America; Yousef El-Laham, Svitlana Vyetrenko, J.P. Morgan, United States of America
Session:
MLSP-L4: Deep Generative Models I Lecture
Track:
Machine Learning for Signal Processing
Location:
Room 101
Presentation Time:
Tue, 16 Apr, 16:50 - 17:10 (UTC +9)
Session Co-Chairs:
Zhihui Zhu, Ohio State University and Vivien Cabannes, Meta
Session MLSP-L4
MLSP-L4.1: Touring sampling with pushforward maps
Vivien Cabannes, Meta, United States of America; Charles Arnal, INRIA, France
MLSP-L4.2: Neural Stochastic Differential Equations with Change Points: A Generative Adversarial Approach
Zhongchang Sun, University at Buffalo, the State University of New York, United States of America; Yousef El-Laham, Svitlana Vyetrenko, J.P. Morgan, United States of America
MLSP-L4.3: GBSD: GENERATIVE BOKEH WITH STAGE DIFFUSION
Jieren Deng, University of Connecticut, United States of America; Xin Zhou, Hao Tian, Zhihong Pan, Baidu USA, United States of America; Derek Aguiar, University of Connecticut, United States of America
MLSP-L4.4: PROGRESSIVE IMAGE SYNTHESIS FROM SEMANTICS TO DETAILS WITH DENOISING DIFFUSION GAN
Guoxing Yang, Haoyu Lu, Chongxuan Li, Renmin University of China, China; Guang Zhou, Haoran Wu, China Unicom Research Institute, China; Zhiwu Lu, Renmin University of China, China
MLSP-L4.5: QUANTUM TOPIC MODEL: TOPIC MODELING USING VARIATIONAL QUANTUM CIRCUITS
Wenbo Qiao, Peng Zhang, Jiaming Zhao, Tianjin University, China; Chang Yang, Shenyang University of Technology, China
MLSP-L4.6: Generative Extension Positive Pairs and Improving Sample Selection Based on Contrastive Learning for Unsupervised Person Re-identification
Zheng-An Zhu, Chen-Kuo Chiang, National Chung Cheng University, Taiwan
Contacts