Skip to main content

Adaptive pooling operators for multiple instance learning

Project description

autopool

Adaptive pooling operators for Multiple Instance Learning (documentation).

PyPI License Build Status Coverage Status Documentation Status PyPI - Python Version

AutoPool is an adaptive (trainable) pooling operator which smoothly interpolates between common pooling operators, such as min-, max-, or average-pooling, automatically adapting to the characteristics of the data.

AutoPool can be readily applied to any differentiable model for time-series label prediction. AutoPool is presented in the following paper, where it is evaluated in conjunction with convolutional neural networks for Sound Event Detection:

Adaptive pooling operators for weakly labeled sound event detection
Brian Mcfee, Justin Salamon, and Juan Pablo Bello
IEEE Transactions on Audio, Speech and Language Processing, In press, 2018.

Project details


Release history Release notifications

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
autopool-0.1.0-py2.py3-none-any.whl (3.8 kB) Copy SHA256 hash SHA256 Wheel py2.py3
autopool-0.1.0.tar.gz (3.3 kB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page