There are 0 repository under ensembles topic.
ML-Ensemble – high performance ensemble learning
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning, ICLR 2020
Uncertainty for deep learning models in PyTorch :seedling:
Python package for tackling multi-class imbalance problems. http://www.cs.put.poznan.pl/mlango/publications/multiimbalance/
Random Forests in Apache Spark
Simple but high-performing method for learning a policy of test-time augmentation
SuperLearner guide: fitting models, ensembling, prediction, hyperparameters, parallelization, timing, feature selection, etc.
Random forests ported to Javascript with WebAssembly and WebWorkers
The PyTorch framework developed to enable my MSci thesis project titled: "Evaluating Uncertainty Estimation Methods For Deep Neural Network’s In Inverse Reinforcement Learning"
Solution for ENS - Societe Generale Challenge (1st place).
Tensorflow slim based model training for ImageCLEF 2016 subfigure classification.
Open-source Survival Analysis library
Utilities for comparing paleoclimate reconstruction ensembles
Repository for Reproducibility for the Paper: "CMA-ES for Post Hoc Ensembling in AutoML: A Great Success and Salvageable Failure".
Repository for Reproducibility for the Paper: "Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML"
Large-scale atmospheric response to Antarctic sea ice loss
We provide two notebooks that enable users to explore and experiment with some BDL techniques as Ensembles, MC Dropout and Laplace Approximation. In this way, they allow you to intuitively visualize the main differences among them in a Simulated Dataset and Boston Dataset.
Methods for increasing generalization ability based on different ways of ensembles building
Tool to analyze two-photon calcium imaging videos, extract neuronal activity, and identify xsembles (ensembles and offsembles).
Predictive Analysis of detecting signal emitting Source
Analysis of Insurance Liability Claim Amount for settlement
Tennis Player strength Analysis using Machine Learning
Testing 21 models (machine learning ensemble) on the WDBC data set
Connecting the Sustainable Development Goals with climate change and the energy transition
Off-the-Shelf Ensemble Systems
Cross-Pollinated Deep Ensembles (NeurIPS Europe Meetup on Bayesian Deep Learning 2020)
This is where I'll post my machine learning templates that I've created
PAMIP simulations to understand role of sea surface temperatures on polar amplifications