Techniques in advanced deep learning provide improvements in one or more of accuracy, performance, and energy efficiency. An array of processing elements comprising a portion of a neural network accelerator performs flow-based computations on wavelets of data. Each processing element has a respective compute element and a respective routing element. Each compute element has a respective floating-point unit enabled to optionally and/or selectively perform floating-point operations in accordance with a programmable exponent bias and/or various floating-point computation variations. In some circumstances, the programmable exponent bias and/or the floating-point computation variations enable neural network processing with improved accuracy, decreased training time, decreased inference latency, and/or increased energy efficiency.