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Ascenoputing's Projects

ncrf icon ncrf

Cancer metastasis detection with neural conditional random field (NCRF)

ncrfpp icon ncrfpp

NCRF++, an Open-source Neural Sequence Labeling Toolkit. It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.

pg icon pg

This repo is the new home of Proof General

pretrained-models.pytorch icon pretrained-models.pytorch

Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.

pyro icon pyro

Deep universal probabilistic programming with Python and PyTorch

pytorch icon pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

pywonderland icon pywonderland

Render beautiful images and animate interesting algorithms in mathematics with Python. Fractals, Penrose tilings, reaction-diffusion, Wilson's uniform spanning tree algorithm, domino shuffling algorithm, coupling from the past, 4D polytopes, Mobius transformations, hyperbolic tilings. www.pywonderland.com.

quantum-svm icon quantum-svm

The quantum circuit version of support vector machine to recognize handwritten 6 and 9

quickseg icon quickseg

(stop maintain)A deep learning Semantic Segmentation scaffolding(图像分割脚手架+模型库)

rdkit icon rdkit

The official sources for the RDKit library

seclists icon seclists

SecLists is the security tester's companion. It's a collection of multiple types of lists used during security assessments, collected in one place. List types include usernames, passwords, URLs, sensitive data patterns, fuzzing payloads, web shells, and many more.

senet icon senet

Squeeze-and-Excitation Networks

sf-zh icon sf-zh

《软件基础》中文版

smartimgprocess icon smartimgprocess

手工实现的智能图片处理系统 包含基础的图片处理功能 各类滤波 seam carving算法 以及结合精细语义分割信息 实现智能去除目标的功能

smpybandits icon smpybandits

🔬 Research Framework for Single and Multi-Players 🎰 Multi-Arms Bandits (MAB) Algorithms, implementing all the state-of-the-art algorithms for single-player (UCB, KL-UCB, Thompson...) and multi-player (MusicalChair, MEGA, rhoRand, MCTop/RandTopM etc).. Available on PyPI: https://pypi.org/project/SMPyBandits/ and documentation on

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