Mixed-signal circuits for embedded machine-learning applications. - Boris Murmann; Daniel Bankman; Elaina Chai; Daisuke Miyashita; Lita Yang (ACSSC, 2015)

An 8-bit, 16 input, 3.2 pJ/op switched-capacitor dot product circuit in 28-nm FDSOI CMOS. - Daniel Bankman; Boris Murmann (A-SSCC, 2016)

BinarEye: An always-on energy-accuracy-scalable binary CNN processor with all memory on chip in 28nm CMOS. - Bert Moons; Daniel Bankman; Lita Yang; Boris Murmann; Marian Verhelst (CICC, 2018)

TRIG: hardware accelerator for inference-based applications and experimental demonstration using carbon nanotube FETs. - Gage Hills; Daniel Bankman; Bert Moons; Lita Yang; Jake Hillard; Alex Kahng; Rebecca Park; Marian Verhelst; Boris Murmann; Max M. Shulaker; H.-S. Philip Wong; Subhasish Mitra (DAC, 2018)

Bit Error Tolerance of a CIFAR-10 Binarized Convolutional Neural Network Processor. - Lita Yang; Daniel Bankman; Bert Moons; Marian Verhelst; Boris Murmann (ISCAS, 2018)

An always-on 3.8μJ/86% CIFAR-10 mixed-signal binary CNN processor with all memory on chip in 28nm CMOS. - Daniel Bankman; Lita Yang; Bert Moons; Marian Verhelst; Boris Murmann (ISSCC, 2018)

RRAM-Based In-Memory Computing for Embedded Deep Neural Networks. - Daniel Bankman; J. Messner; Albert Gural; Boris Murmann (ACSSC, 2019)

An Always-On 3.8 $ mu$ J/86% CIFAR-10 Mixed-Signal Binary CNN Processor With All Memory on Chip in 28-nm CMOS. - Daniel Bankman; Lita Yang; Bert Moons; Marian Verhelst; Boris Murmann (IEEE J. Solid State Circuits, 2019)