68 citations · 68 across the 4 of their papers we have counts for
4 papers
Target-independent XLA optimization using Reinforcement Learning
Milan Ganai, Haichen Li, Theodore Enns +2
An important challenge in Machine Learning compilers like XLA is multi-pass optimization and analysis. There has been recent interest chiefly in XLA target-dependent optimization o…
A Density Functional Tight Binding Layer for Deep Learning of Chemical Hamiltonians
Haichen Li, Christopher Collins, Matteus Tanha +2
Current neural networks for predictions of molecular properties use quantum chemistry only as a source of training data. This paper explores models that use quantum chemistry as an…
Tuning the Molecular Weight Distribution from Atom Transfer Radical Polymerization Using Deep Reinforcement Learning
Haichen Li, Christopher R. Collins, Thomas G. Ribelli +4
We devise a novel technique to control the shape of polymer molecular weight distributions (MWDs) in atom transfer radical polymerization (ATRP). This technique makes use of recent…
Embedding parameters in ab initio theory to develop approximations based on molecular similarity
Matteus Tanha, Haichen Li, Shiva Kaul +3
A means to take advantage of molecular similarity to lower the computational cost of electronic structure theory is explored, in which parameters are embedded into a low-cost, low-…