[PyTorch]
github.comImageNet classification using binary Convolutional Neural Networks
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DUCKQUANT / THE QUANT & AI DIRECTORY
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ImageNet classification using binary Convolutional Neural Networks
Caffe implementation of accurate low-precision neural networks
Publication: Training deep neural networks with low precision multiplications. Published Dec 22, 2014.
Publication: 8-Bit Approximations for Parallelism in Deep Learning. Published Nov 14, 2015.
Publication: Bitwise Neural Networks. Published Jan 22, 2016.
Publication: Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift. Published Feb 11, 2015.
Publication: Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1. Published Feb 9, 2016.
Publication: Layer Normalization. Published Jul 21, 2016.
Publication: Convolutional Neural Networks using Logarithmic Data Representation. Published Mar 3, 2016.
Publication: Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations. Published Sep 22, 2016.
Publication: Training Bit Fully Convolutional Network for Fast Semantic Segmentation. Published Dec 1, 2016.
Publication: Recurrent Neural Networks With Limited Numerical Precision. Published Aug 24, 2016.
Publication: Sigma Delta Quantized Networks. Published Nov 7, 2016.
Publication: Effective Quantization Methods for Recurrent Neural Networks. Published Nov 30, 2016.
Publication: QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding. Published Oct 7, 2016.
Publication: Fixed-Point Performance Analysis of Recurrent Neural Networks. Published Dec 4, 2015.
Publication: Quantized Convolutional Neural Networks for Mobile Devices. Published Dec 21, 2015.
Publication: Fixed Point Quantization of Deep Convolutional Networks. Published Nov 19, 2015.
Training Deep Neural Networks with binary weights during propagations
Source code for ``Neural Networks with Few Multiplications'' published at ICLR 2016
Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1
Publication: Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation. Published Aug 15, 2013.
Publication: Compressing Deep Convolutional Networks using Vector Quantization. Published Dec 18, 2014.
Publication: Resiliency of Deep Neural Networks under Quantization. Published Nov 20, 2015.
Publication: Training Binary Multilayer Neural Networks for Image Classification using Expectation Backpropagation. Published Mar 12, 2015.
Publication: Rounding Methods for Neural Networks with Low Resolution Synaptic Weights. Published Apr 22, 2015.
We show empirically that in SGD training of deep neural networks, one can, at no or nearly no loss of accuracy, quantize the gradients…
The official Python client library for the Massive.com REST and WebSocket API.
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