Highly optimized inference engine for Binarized Neural Networks
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Updated
Aug 9, 2024 - C++
Highly optimized inference engine for Binarized Neural Networks
Optimization of Transmit Beamforming based on Unsupervised Learning With Channel Covariances for MISO Downlink Assisted by Reconfigurable Intelligent Surfaces
High-Performance Binary Neural Networks for MNIST Classification: From Software to ASIC
A toolbox for spectral compressive imaging reconstruction including MST (CVPR 2022), CST (ECCV 2022), DAUHST (NeurIPS 2022), BiSCI (NeurIPS 2023), HDNet (CVPR 2022), MST++ (CVPRW 2022), etc.
Repository for testing Binary Neurons Network in the 3d world
Bayesian Neural Network in PyTorch
Repo for my thesis research development at UC Riverside: "Classifying Galaxy Morphologies Using Bayesian Neural Networks for LSST"
A Toolbox for Binarized Spectral Compressive Imaging (NeurIPS 2023)
This project is the official implementation of 'Basic Binary Convolution Unit for Binarized Image Restoration Network', ICLR2023
A PyTorch implemenation of real XNOR-popcount (1-bit op) GEMM Linear PyTorch extension support both CPU and CUDA
Neural Property Approximate Quantifier
The official repository for the paper LAB: Learnable Activation Binarizer for Binary Neural Networks.
BiDet implement
Towards Accurate Binary Neural Networks via Modeling Contextual Dependencies
[ICCV 2021] Code release for "Sub-bit Neural Networks: Learning to Compress and Accelerate Binary Neural Networks"
This is a framework for binary neural network based mmclassification
Exploring the link between uncertainty estimates obtained via "exact" Bayesian inference and out-of-distribution (OOD) detection.
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