I'm so happy that @rachelmetz included the dog poop example in her explanation of #algorithms : https://t.co/0kVEW1NG6s But also -- this article does a great job of explaining what algorithms are and why they matter! 🤓
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Pasquale Minervini    @PMinervini    12/6/2021      

If you think that back-propagating through algorithms is your thing, make sure to check our presentation (https://t.co/csD9hnRvx7), and @ykilcher's amazing paper explanation! (https://t.co/JinSwYIJtR)
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Tal Schuster    @TalSchuster    11/30/2021      

A great video explaining our recent ExT5 paper by the legend @ykilcher
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CopeNLU    @CopeNLU    12/1/2021      

In "Diagnostics-Guided Explanation Generation", we demonstrate how optimising for diagnostic properties of explanations -- faithfulness, data consistency, confidence indication -- can improve explanation quality https://t.co/0BN3a8VW97 @atanasovapepa @IAugenstein #AAAI2022
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TheSequence    @TheSequenceAI    11/24/2021      

learn2learn is a software library for meta-learning research. It accelerates 2 aspects: 1. fast prototyping 2. correct reproducibility With learn2learn you can: 1. Create new algorithms and domains 2. Implement existing algorithms and standardized benchmarks
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