ML framework

DYNET 1701.03980 ABS cpp backend lw graph representation Problems easier debugging / maintaining large proj. express naturally Static vs Dynamic static pre-written model transfered to computation graph graph can be well optimized cannot deal with variable input size. NLP RNN cannot deal with variable input structure. Tree NN, Graph NN hard for complex flow-contronl logic (interface design) nontrivial interface. debug difficulty during execution dynamic do computation on the fly can be expensiveo flow control and variable sized inputs are in host language (python?...