76 citations · 214 across the 9 of their papers we have counts for
9 papers
Blip-Up Blip-Down Circular EPI (BUDA-cEPI) for Distortion-Free dMRI with Rapid Unrolled Deep Learning Reconstruction
Uten Yarach, Itthi Chatnuntawech, Congyu Liao +9
Purpose: We implemented the blip-up, blip-down circular echo planar imaging (BUDA-cEPI) sequence with readout and phase partial Fourier to reduced off-resonance effect and T2* blur…
StitchNet: Composing Neural Networks from Pre-Trained Fragments
Surat Teerapittayanon, Marcus Comiter, Brad McDanel +1
We propose StitchNet, a novel neural network creation paradigm that stitches together fragments (one or more consecutive network layers) from multiple pre-trained neural networks.…
DaiMoN: A Decentralized Artificial Intelligence Model Network
Surat Teerapittayanon, H. T. Kung
We introduce DaiMoN, a decentralized artificial intelligence model network, which incentivizes peer collaboration in improving the accuracy of machine learning models for a given c…
CheckNet: Secure Inference on Untrusted Devices
Marcus Comiter, Surat Teerapittayanon, H. T. Kung
We introduce CheckNet, a method for secure inference with deep neural networks on untrusted devices. CheckNet is like a checksum for neural network inference: it verifies the integ…
Incomplete Dot Products for Dynamic Computation Scaling in Neural Network Inference
Bradley McDanel, Surat Teerapittayanon, H. T. Kung
We propose the use of incomplete dot products (IDP) to dynamically adjust the number of input channels used in each layer of a convolutional neural network during feedforward infer…
Embedded Binarized Neural Networks
Bradley McDanel, Surat Teerapittayanon, H. T. Kung
We study embedded Binarized Neural Networks (eBNNs) with the aim of allowing current binarized neural networks (BNNs) in the literature to perform feedforward inference efficiently…