5 papers
DIM: Enforcing Domain-Informed Monotonicity in Deep Neural Networks
Joshua Salim, Jordan Yu, Xilei Zhao
While deep learning models excel at predictive tasks, they often overfit due to their complex structure and large number of parameters, causing them to memorize training data, incl…
Compressive Imaging Reconstruction via Tensor Decomposed Multi-Resolution Grid Encoding
Zhenyu Jin, Yisi Luo, Xile Zhao +1
Compressive imaging (CI) reconstruction, such as snapshot compressive imaging (SCI) and compressive sensing magnetic resonance imaging (MRI), aims to recover high-dimensional image…
Continuous Representation Methods, Theories, and Applications: An Overview and Perspectives
Yisi Luo, Xile Zhao, Deyu Meng
Recently, continuous representation methods emerge as novel paradigms that characterize the intrinsic structures of real-world data through function representations that map positi…
Cross-Frequency Implicit Neural Representation with Self-Evolving Parameters
Chang Yu, Yisi Luo, Kai Ye +2
Implicit neural representation (INR) has emerged as a powerful paradigm for visual data representation. However, classical INR methods represent data in the original space mixed wi…
NeurTV: Total Variation on the Neural Domain
Yisi Luo, Xile Zhao, Kai Ye +1
Recently, we have witnessed the success of total variation (TV) for many imaging applications. However, traditional TV is defined on the original pixel domain, which limits its pot…