18 citations · 69 across the 20 of their papers we have counts for
5 papers · 1 filter
Blaschke Product Neural Networks (BPNN): A Physics-Infused Neural Network for Phase Retrieval of Meromorphic Functions
Juncheng Dong, Simiao Ren, Yang Deng +5
Numerous physical systems are described by ordinary or partial differential equations whose solutions are given by holomorphic or meromorphic functions in the complex domain. In ma…
Task Affinity with Maximum Bipartite Matching in Few-Shot Learning
Cat P. Le, Juncheng Dong, Mohammadreza Soltani +1
We propose an asymmetric affinity score for representing the complexity of utilizing the knowledge of one task for learning another one. Our method is based on the maximum bipartit…
A Methodology for Exploring Deep Convolutional Features in Relation to Hand-Crafted Features with an Application to Music Audio Modeling
Anna K. Yanchenko, Mohammadreza Soltani, Robert J. Ravier +2
Understanding the features learned by deep models is important from a model trust perspective, especially as deep systems are deployed in the real world. Most recent approaches for…
Fisher Task Distance and Its Application in Neural Architecture Search
Cat P. Le, Mohammadreza Soltani, Juncheng Dong +1
We formulate an asymmetric (or non-commutative) distance between tasks based on Fisher Information Matrices, called Fisher task distance. This distance represents the complexity of…
Improved Automated Machine Learning from Transfer Learning
Cat P. Le, Mohammadreza Soltani, Robert Ravier +1
In this paper, we propose a neural architecture search framework based on a similarity measure between some baseline tasks and a target task. We first define the notion of the task…