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ML Sessions 2019
MCMC #1 - 7. Feb. 2019 An Introduction to MCMC for Machine Learning
fhttps://www.cs.ubc.ca/~arnaud/andrieu_defreitas_doucet_jordan_intromontecarlomachinelearning.pdf
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Interpretable ML #6 - Application Session 24. Jan. 2019 e-SNLI: Natural Language Inference with Natural Language Explanations Judith Petra How do Humans Understand Explanations from Machine Learning Systems? An Evaluation of the Human-Interpretability of Explanation Sanne Sarah Methods for Interpreting and Understanding Deep Neural Networks Federico Matteo Network Disection: Quantifying Interpretability of Deep Visual Representations Louise Gradcam++ Sofia Marcus Interpretable ML #5 - 7. Jan. 2019 A causal framework for explaining the predictions of black-box sequence-to-sequence models
https://people.csail.mit.edu/tommi/papers/AlvJaa_EMNLP2017.pdf