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31 Documents (Short List) 
Russ Salakhutdinov sur Twitter : "Are Model Explanations Useful in Practice? Rethinking How to Support Human-ML Interactions..."
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2023-04-02 About
[2301.04709] Causal Abstraction for Faithful Model Interpretation
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2023-01-14 About
[2207.05221] Language Models (Mostly) Know What They Know
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2022-09-15 About
[2011.06225] A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges
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2022-09-08 About
[2010.00711] A Survey of the State of Explainable AI for Natural Language Processing
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2022-09-08 About
[2008.07267] A Survey of Active Learning for Text Classification using Deep Neural Networks
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2022-09-06 About
Rajiv Shah sur Twitter : "How to explain predictions from 🤗 transformer models?..."
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2022-08-18 About
Why generative modeling
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2021-01-12 About
[2007.04612] Concept Bottleneck Models
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2020-07-10 About
[2006.09462] Selective Question Answering under Domain Shift
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2020-06-30 About
[1912.08422] Distilling Structured Knowledge into Embeddings for Explainable and Accurate Recommendation
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2020-05-12 About
[2004.14843] Knowledge Graph Embeddings and Explainable AI
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2020-05-04 About
[2004.14545] Explainable Deep Learning: A Field Guide for the Uninitiated
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2020-05-01 About
Max Little sur Twitter : "Causal bootstrapping - a simple way of doing causal inference using arbitrary machine learning algo..."
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2020-03-08 About
Interpretable Named entity recognition with keras and LIME – Depends on the definition
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2020-01-09 About
[1905.11852] EDUCE: Explaining model Decisions through Unsupervised Concepts Extraction
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2019-12-05 About
Bayesian deep learning with Fastai : how not to be uncertain about your uncertainty !
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2019-11-29 About
Artificial Human Intelligence: The Programmer’s Apprentice - Tom Dean and Rishabh Singh - Google Research
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2019-11-16 About
[1506.02142] Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
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2019-05-13 About
Uncertainty estimation for Neural Network — Dropout as Bayesian Approximation
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2019-05-13 About
Durk Kingma sur Twitter : about likelihood-based generative models
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2018-12-07 About
Making Your Neural Network Say “I Don’t Know” — Bayesian NNs using Pyro and PyTorch
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2018-12-04 About
Trying to Understand Recurrent Neural Networks for Language Processing (slides)
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2018-11-11 About
PROCEEDINGS of the BlackboxNLP Workshop
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2018-11-06 About
Analyzing and interpreting neural networks for NLP (Workshop's Home page)
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2018-11-06 About
Deep Bayesian Neural Networks. – Stefano Cosentino – Medium
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2018-11-05 About
Deep Learning Is Not Good Enough, We Need Bayesian Deep Learning for Safe AI - Home
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2018-11-05 About
Trying to Understand Recurrent Neural Networks for Language Processing (tweets)
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2018-11-01 About
GitHub - marcotcr/lime: Lime: Explaining the predictions of any machine learning classifier
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2018-09-09 About
[1602.04938] "Why Should I Trust You?": Explaining the Predictions of Any Classifier
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2018-09-09 About
The Dark Secret at the Heart of AI - MIT Technology Review
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2017-12-31 About
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