Flows for Flows: Training Normalizing Flows Between Arbitrary Distributions with Maximum Likelihood Estimation

4 November 2022

Papers citing "Flows for Flows: Training Normalizing Flows Between Arbitrary Distributions with Maximum Likelihood Estimation"

7 / 7 papers shown

Title
Machine Learning for Anomaly Detection in Particle Physics Vasilis Belis Patrick Odagiu Thea Klæboe Årrestad 30 40 0 20 Dec 2023
Arbitrary Distributions Mapping via SyMOT-Flow: A Flow-based Approach Integrating Maximum Mean Discrepancy and Optimal Transport Zhe Xiong Qiaoqiao Ding Xiaoqun Zhang OOD 13 0 0 26 Aug 2023
Decorrelation using Optimal Transport M. Algren J. A. Raine T. Golling OT 23 1 0 11 Jul 2023
Probabilistic and Semantic Descriptions of Image Manifolds and Their Applications Peter Tu Zhaoyuan Yang Richard I. Hartley Zhiwei Xu Jing Zhang Yiwei Fu Dylan Campbell Jaskirat Singh Tianyu Wang DiffM 22 2 0 06 Jul 2023
CURTAINs Flows For Flows: Constructing Unobserved Regions with Maximum Likelihood Estimation Debasish Sengupta Samuel Klein J. A. Raine T. Golling OOD 13 27 0 08 May 2023
Decorrelation with conditional normalizing flows Samuel Klein T. Golling 16 4 0 04 Nov 2022
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization Chin-Wei Huang Ricky T. Q. Chen Christos Tsirigotis Aaron Courville OT 112 95 0 10 Dec 2020