120 citations · 223 across the 24 of their papers we have counts for
4 papers · 1 filter
Deep Learning Evidence for Global Optimality of Gerver's Sofa
Kuangdai Leng, Jia Bi, Jaehoon Cha +2
The Moving Sofa Problem, formally proposed by Leo Moser in 1966, seeks to determine the largest area of a two-dimensional shape that can navigate through an -shaped corridor wit…
Zero Coordinate Shift: Whetted Automatic Differentiation for Physics-informed Operator Learning
Kuangdai Leng, Mallikarjun Shankar, Jeyan Thiyagalingam
Automatic differentiation (AD) is a critical step in physics-informed machine learning, required for computing the high-order derivatives of network output w.r.t. coordinates of co…
Disentangling Autoencoders (DAE)
Jaehoon Cha, Jeyan Thiyagalingam
Noting the importance of factorizing (or disentangling) the latent space, we propose a novel, non-probabilistic disentangling framework for autoencoders, based on the principles of…
Scientific Machine Learning Benchmarks
Jeyan Thiyagalingam, Mallikarjun Shankar, Geoffrey Fox +1
The breakthrough in Deep Learning neural networks has transformed the use of AI and machine learning technologies for the analysis of very large experimental datasets. These datase…