DUCKQUANT / THE QUANT & AI DIRECTORY
1,058 resources, ranked by in-directory PageRank
Publication: What is the State of Neural Network Pruning?. Published Mar 6, 2020.
Publication: A Statistical Framework for Low-bitwidth Training of Deep Neural Networks. Published Oct 27, 2020.
Publication: Towards Fast and Energy-Efficient Binarized Neural Network Inference on FPGA. Published Oct 4, 2018.
Publication: ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware. Published Dec 2, 2018.
Publication: Variational Information Distillation for Knowledge Transfer. Published Apr 11, 2019.
Publication: Fighting Quantization Bias With Bias. Published Jun 7, 2019.
Publication: Circulant Binary Convolutional Networks: Enhancing the Performance of 1-bit DCNNs with Circulant Back Propagation. Published Oct 24, 2019.
Publication: SWALP : Stochastic Weight Averaging in Low-Precision Training. Published Apr 26, 2019.
Publication: Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design. Published Feb 1, 2019.
Publication: Low-bit Quantization of Neural Networks for Efficient Inference. Published Feb 18, 2019.
Publication: HAQ: Hardware-Aware Automated Quantization With Mixed Precision. Published 2019.
Publication: daBNN: A Super Fast Inference Framework for Binary Neural Networks on ARM devices. Published Aug 16, 2019.
Publication: QKD: Quantization-aware Knowledge Distillation. Published Nov 28, 2019.
Publication: Mixed Precision Quantization of ConvNets via Differentiable Neural Architecture Search. Published Nov 30, 2018.
Publication: The Knowledge Within: Methods for Data-Free Model Compression. Published Dec 3, 2019.
Publication: Regularizing Activation Distribution for Training Binarized Deep Networks. Published Apr 4, 2019.
Publication: Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks. Published Sep 28, 2019.
Publication: Mixed Precision Training With 8-bit Floating Point. Published May 29, 2019.
Publication: Accurate and Compact Convolutional Neural Networks with Trained Binarization. Published Sep 25, 2019.
Publication: Knowledge distillation for optimization of quantized deep neural networks. Published Sep 4, 2019.
Publication: Training High-Performance and Large-Scale Deep Neural Networks with Full 8-bit Integers. Published Sep 5, 2019.
Publication: MoBiNet: A Mobile Binary Network for Image Classification. Published Jul 29, 2019.
Publication: Back to Simplicity: How to Train Accurate BNNs from Scratch?. Published Jun 19, 2019.
Publication: Matrix and tensor decompositions for training binary neural networks. Published Apr 16, 2019.
Publication: Binarized Neural Architecture Search. Published Nov 25, 2019.
Publication: Improved training of binary networks for human pose estimation and image recognition. Published Apr 11, 2019.
Publication: TentacleNet: A Pseudo-Ensemble Template for Accurate Binary Convolutional Neural Networks. Published Dec 20, 2019.
Publication: RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs. Published Aug 21, 2019.
Publication: Mixed Precision Training of Convolutional Neural Networks using Integer Operations. Published Feb 3, 2018.
Publication: AMC: AutoML for Model Compression and Acceleration on Mobile Devices. Published Feb 10, 2018.
Publication: Moonshine: Distilling with Cheap Convolutions. Published Nov 7, 2017.
Publication: A Quantization-Friendly Separable Convolution for MobileNets. Published Mar 22, 2018.
Publication: Inference of Quantized Neural Networks on Heterogeneous All-Programmable Devices. Published Jun 21, 2018.
Publication: FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks. Published Sep 12, 2018.
Abstract page for arXiv paper 1902.01917: Same, Same But Different - Recovering Neural Network Quantization Error Through Weight Factorization
Publication: Learned Step Size Quantization. Published Feb 21, 2019.
