Week 4 - Reproducibility In Machine Learning: From Theory To Practice - Koustuv Sinha

Week 4 - Reproducibility in Machine Learning: From Theory to Practice - Koustuv Sinha

MICCAI Hackathon 2020: Keynote Koustuv Sinha - Reproducibility in Machine Learning

MICCAI Hackathon

ReproducedPapers.org: Openly teaching and structuring machine learning reproducibility

Computer Vision Lab TU-Delft

Provenance and Reproducibility in Machine Learning; what is it and why you need it?

MLOps.community

Reproducibility and Extendibility Best Practices for Machine Learning

Boston Data Science Meetup

Reproducibility in Machine Learning, Challenge in Machine Learning

Harpreet Sahota

Machine Learning Pipelines: Provenance, Reproducibility and FAIR Data Principles - S.Samuel

Deep Learning Reproducibility with TensorFlow

Aurélien Géron

useR! 2020: Keynote - Computational Reproducibility, from Theory to Practice (Anna Krystalli)

Reproducibility, Reusability, & Robustness in Deep Reinforcement Learning - Prof. Pineau

The Artificial Intelligence Channel

Reproducibility in Machine Learning Workshop (ICML 2017)

The Nutty Netter (Alex Lamb)

Towards Training Reproducible Deep Learning Models

Boyuan Chen (Nemo)

3. Reproducible machine learning of movement behaviours from wearable sensors - Aiden Doherty

Evaluating Logical Generalization in Graph Neural Networks with Koustuv Sinha

Weights & Biases

Joelle Pineau: Reproducibility, Reusability, and Robustness in Deep Reinforcement Learning ICLR 2018

Steven Van Vaerenbergh

Reproducibility in Deep Reinforcement Learning - Prof. Pineau - NIPS2017

The Artificial Intelligence Channel