70 skills found · Page 1 of 3
Dao-AILab / Fast Hadamard TransformFast Hadamard transform in CUDA, with a PyTorch interface
yuanli2333 / Hadamard Matrix For HashingCVPR2020/TNNLS2023: Central Similarity Quantization/Hashing for Efficient Image and Video Retrieval
sniklaus / Pytorch Extensionan example of a CUDA extension for PyTorch using CuPy which computes the Hadamard product of two tensors
FALCONN-LIB / FFHTFast Fast Hadamard Transform
jnhwkim / MulLowBiVQAHadamard Product for Low-rank Bilinear Pooling
videlanicolas / QKDPython simulation of protocol BB84 for QKD.
williamdelacruz / Single Pixel ImagingSingle Pixel Imaging with Hadamard basis
JuliaMath / Hadamard.jlFast Walsh-Hadamard transforms for the Julia language
cbasedlf / Single Pixel DemoDemo for single-pixel imaging using Hadamard functions as sensing basis. Matlab/Python implementations
IST-DASLab / HALOHALO: Hadamard-Assisted Low-Precision Optimization and Training method for finetuning LLMs. 🚀 The official implementation of https://arxiv.org/abs/2501.02625
nbarbey / FhtFast Hadamard Transform
dingluo / FwhtFast Walsh Hadamard Transform in Python
thaihungle / SHMSource code for Stable Hadamard Memory
dell / JltJohnson-Lindenstrauss transform (JLT), random projections (RP), fast Johnson-Lindenstrauss transform (FJLT), and randomized Hadamard transform (RHT) in python 3.x
zibangzhang / Hadamard Single Pixel ImagingSingle-pixel imaging using Hadamard basis patterns
mbitsnbites / HimgHadamard based lossy image compression
ZYangChen / HARTThe official implementation of "Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer"
LCAV / SparseFHTA Fast Hadamard Transform for Signals with Sub-linear Sparsity in the Transform Domain -- Implementation
werringwu / SASW[ACM MM'25 Oral] A Novel Perspective on Low-Light Image Enhancement: Leveraging Artifact Regularization and Walsh-Hadamard Transform (SASW)
zitengsun / Hadamard ResponseHadamard Response: Communication efficient, sample optimal, linear time locally private learning of distributions
