26 citations · 36 across the 4 of their papers we have counts for
4 papers
FNetAR: Mixing Tokens with Autoregressive Fourier Transforms
Tim Lou, Michael Park, Mohammad Ramezanali +1
In this note we examine the autoregressive generalization of the FNet algorithm, in which self-attention layers from the standard Transformer architecture are substituted with a tr…
Moment-Matching Graph-Networks for Causal Inference
Michael Park
In this note we explore a fully unsupervised deep-learning framework for simulating non-linear structural equation models from observational training data. The main contribution of…
SQuantizer: Simultaneous Learning for Both Sparse and Low-precision Neural Networks
Mi Sun Park, Xiaofan Xu, Cormac Brick
Deep neural networks have achieved state-of-the-art accuracies in a wide range of computer vision, speech recognition, and machine translation tasks. However the limits of memory b…
Hybrid Pruning: Thinner Sparse Networks for Fast Inference on Edge Devices
Xiaofan Xu, Mi Sun Park, Cormac Brick
We introduce hybrid pruning which combines both coarse-grained channel and fine-grained weight pruning to reduce model size, computation and power demands with no to little loss in…