33 citations · 68 across the 8 of their papers we have counts for
5 papers · 1 filter
Uncovering Closed-form Governing Equations of Nonlinear Dynamics from Videos
Lele Luan, Yang Liu, Hao Sun
Distilling analytical models from data has the potential to advance our understanding and prediction of nonlinear dynamics. Although discovery of governing equations based on obser…
Synthetic Benchmarks for Scientific Research in Explainable Machine Learning
Yang Liu, Sujay Khandagale, Colin White +1
As machine learning models grow more complex and their applications become more high-stakes, tools for explaining model predictions have become increasingly important. This has spu…
Physics-informed Spline Learning for Nonlinear Dynamics Discovery
Fangzheng Sun, Yang Liu, Hao Sun
Dynamical systems are typically governed by a set of linear/nonlinear differential equations. Distilling the analytical form of these equations from very limited data remains intra…
How Powerful are Performance Predictors in Neural Architecture Search?
Colin White, Arber Zela, Binxin Ru +2
Early methods in the rapidly developing field of neural architecture search (NAS) required fully training thousands of neural networks. To reduce this extreme computational cost, d…
Large-scale empirical validation of Bayesian Network structure learning algorithms with noisy data
Anthony C. Constantinou, Yang Liu, Kiattikun Chobtham +2
Numerous Bayesian Network (BN) structure learning algorithms have been proposed in the literature over the past few decades. Each publication makes an empirical or theoretical case…