2 citations · 2 across the 4 of their papers we have counts for
6 papers
Learning Heat Diffusion for Network Alignment
Sisi Qu, Mengmeng Xu, Bernard Ghanem +1
Networks are abundant in the life sciences. Outstanding challenges include how to characterize similarities between networks, and in extension how to integrate information across n…
Algorithmic Probability-guided Supervised Machine Learning on Non-differentiable Spaces
Santiago Hernández-Orozco, Hector Zenil, Jürgen Riedel +3
We show how complexity theory can be introduced in machine learning to help bring together apparently disparate areas of current research. We show that this new approach requires l…
Synthesizing New Retinal Symptom Images by Multiple Generative Models
Yi-Chieh Liu, Hao-Hsiang Yang, Chao-Han Huck Yang +5
Age-Related Macular Degeneration (AMD) is an asymptomatic retinal disease which may result in loss of vision. There is limited access to high-quality relevant retinal images and po…
Controllability, Multiplexing, and Transfer Learning in Networks using Evolutionary Learning
Rise Ooi, Chao-Han Huck Yang, Pin-Yu Chen +5
Networks are fundamental building blocks for representing data, and computations. Remarkable progress in learning in structurally defined (shallow or deep) networks has recently be…
Predictive Systems Toxicology
Narsis A. Kiani, Ming-Mei Shang, Hector Zenil +1
In this review we address to what extent computational techniques can augment our ability to predict toxicity. The first section provides a brief history of empirical observations…
HiDi: An efficient reverse engineering schema for large scale dynamic regulatory network reconstruction using adaptive differentiation
Yue Deng, Hector Zenil, Jesper Tégner +1
The use of differential equations (ODE) is one of the most promising approaches to network inference. The success of ODE-based approaches has, however, been limited, due to the dif…