berry1111

berry1111

Geek Repo

Github PK Tool:Github PK Tool

berry1111's repositories

MTL_-

学习并复现经典的推荐系统多目标任务,如:SharedBottom、ESMM、MMoE、PLE

Language:Jupyter NotebookStargazers:1Issues:0Issues:0

Airline-Mutli-Task-Learning

基于多任务学习的机票价格预测模型

Language:PythonStargazers:0Issues:0Issues:0

bank_interview

:bank: 银行笔试面试经验分享及资料分享(help you pass the bank interview, and get a amazing bank offer!)

Stargazers:0Issues:0Issues:0

Bayesian-Neural-Networks

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

Language:Jupyter NotebookLicense:MITStargazers:0Issues:0Issues:0
Language:Jupyter NotebookStargazers:0Issues:0Issues:0

bayesianLSTM

Bayesian LSTM (Tensorflow)

Language:PythonStargazers:0Issues:0Issues:0

BayesianLSTM-for-Time-series-Prediction

Bayesian LSTM for time-series prediction.

Language:Jupyter NotebookLicense:Apache-2.0Stargazers:0Issues:1Issues:0

bgd

Implementation of Bayesian Gradient Descent

Language:PythonLicense:MITStargazers:0Issues:0Issues:0

blitz-bayesian-deep-learning

A simple and extensible library to create Bayesian Neural Network layers on PyTorch.

Language:PythonLicense:GPL-3.0Stargazers:0Issues:0Issues:0

CodingInterviews

剑指Offer——名企面试官精讲典型编程题

Language:C++License:GPL-3.0Stargazers:0Issues:0Issues:0

LSTM-Autoencoder-for-Anomaly-Detection

AI deep learning neural network for anomaly detection using Python, Keras and TensorFlow

Stargazers:0Issues:0Issues:0

LSTMAE

SPATIAL-TEMPORAL DATA AUGMENTATION BASED ON LSTM AUTOENCODER NETWORK FOR SKELETON-BASED HUMAN ACTION RECOGNITION

Stargazers:0Issues:0Issues:0

MachineLearning_Python

机器学习算法python实现

License:MITStargazers:0Issues:0Issues:0

PBC-ClinicalStudy

Survival Analysis and Cox Proportional-Hazards Model

License:MITStargazers:0Issues:0Issues:0

PyTorch-BayesianCNN

Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

License:MITStargazers:0Issues:0Issues:0

Uncertainty-Estimation-BNN

Epistemic Uncertainty Estimation with Monte Carlo Dropout

Stargazers:0Issues:0Issues:0

vadam

Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, Gal, and Srivastava

Stargazers:0Issues:0Issues:0