no code implementations • 22 May 2024 • Qiuyi Chen, Panagiotis Tsilifis, Mark Fuge
Recently, generative models such as Generative Adversarial Networks (GANs) have shown great potential in approximating complex high dimensional conditional distributions and have paved the way for characterizing posterior densities in Bayesian inverse problems, yet the problems' high dimensionality and high nonlinearity often impedes the model's training.
1 code implementation • 27 Apr 2024 • Qiuyi Chen, Mark Fuge
This paper introduces Least Volume-a simple yet effective regularization inspired by geometric intuition-that can reduce the necessary number of latent dimensions needed by an autoencoder without requiring any prior knowledge of the intrinsic dimensionality of the dataset.
1 code implementation • 26 Mar 2024 • Haiyang Zhang, Qiuyi Chen, Yuanjie Zou, Yushan Pan, Jia Wang, Mark Stevenson
The Document Set Expansion (DSE) task involves identifying relevant documents from large collections based on a limited set of example documents.
no code implementations • 20 Jan 2024 • Haiyang Zhang, Qiuyi Chen, Yuanjie Zou, Yushan Pan, Jia Wang, Mark Stevenson
Previous work shows that PU learning is a promising method for this task.