by GCBC Ventures | Apr 3, 2020 | Machine Learning

GPyOpt Python Package Using GPyOpt Best Result and Ensembling Results Code 1. GPyOpt Python Package GPyOpt is a Python open-source library for Bayesian Optimization developed by the Machine Learning group of the University of Sheffield. It is based on GPy, a Python...
by GCBC Ventures | Mar 22, 2020 | Machine Learning, Papers

In this work, the authors present a simpler alternative, “a simple linear model w.r.t. the adjacency matrix of the graph”, to graph convolution encoders for graph autoencoders. Embedding vectors are obtained by multiplying the n × n normalized adjacency...
by GCBC Ventures | Mar 15, 2020 | Machine Learning

Paper: Optuna: A Next-generation Hyperparameter Optimization Framework – Akiba et al 2019 Hyperparameter Search With Optuna: Part 1 – Scikit-learn Classification and Ensembling Hyperparameter Search With Optuna: Part 2 – XGBoost Classification and Ensembling...
by GCBC Ventures | Feb 28, 2020 | Machine Learning, Papers

A new message passing graph neural network with attention is presented here as applied to small molecule predictive machine learning tasks. In this paper, we describe a self-attention-based message-passing neural network (SAMPN) model, which is a modification of...
by GCBC Ventures | Feb 24, 2020 | Machine Learning

Paper: Optuna: A Next-generation Hyperparameter Optimization Framework – Akiba et al 2019 Hyperparameter Search With Optuna: Part 1 – Scikit-learn Classification and Ensembling Hyperparameter Search With Optuna: Part 2 – XGBoost Classification and Ensembling...