dengniran Goto Github PK

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知乎文本摘要

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单变量多元方差分析

-competition-baseline

人脸年龄识别baseline

bayesian-neural-networks

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

bct-nsp

bphgnn-23

dcrs

DCRS: Encoding Node Diffusion Competence and Role Significance for Network Dismantling

deepim

dismantlingcommunity

Python code for dismantling network using a community based approach

dualnetgnn

gdm

Repository of the paper "Machine learning dismantling and early-warning signals of disintegration in complex systems" by M. Grassia, M. De Domenico and G. Mangioni

graph-based-deep-learning-literature

links to conference publications in graph-based deep learning

hgsr

Implement of our TKDE paper: Hyperbolic Graph Learning for Social Recommendation

hmsg

HMSG: Heterogeneous graph neural network based on metapath subgraph learning

information-diffusion-boundaries-in-code-review

Replication package for "Upper Bound of Information Diffusion in Code Review"

iris_classification_bpneuralnetwork

Python 基于BP神经网络实现鸢尾花的分类

lstm_poem

使用pytorch实现RNN-LSTM写诗

mec_drl

Deep reinforcement learning for mobile edge computing

meta-gnn

Implementation of Meta-GNN in TensorFlow

metaheuristic-flower_pollination_algorithm

Flower Pollination Algorithm to Minimize Functions with Continuous Variables

mgnn

modeling_complex_networks

Modeling complex networks: An implementation based on Python+NetworkX

motif-based-inductive-gnn-training

multiplex-plot

Multiplex: visualizations that tell stories—A Python library to create and annotate beautiful network graph visualizations, text visualizations and more.

multivariate-multi-step-time-series-forecasting-via-lstm

多元多步时间序列的LSTM模型预测——基于Keras

nees

Neural extraction of multiscale essential structure for network dismantling

network_dismantling

Network Dismantling Project

neural-subgraph-learning-gnn

nirm

NIRM: Dismantling Complex Networks by a Neural Model Trained from Tiny Networks

nnesf

Official implementation of Elementary Subgraph Features for Link Prediction with Neural Networks