AI DIGEST #NOVEMBER20

By Alisher Abdulkhaev Issue #17: November 2020 AlphaFold: a solution to a 50-year-old grand challenge in biology The latest version of AlphaFold (AlphaFold-2) has been recognised as a solution to one of biology's grand challenges - the “protein folding problem”.It was validated at CASP14, the biennial Critical Assessment of protein Structure PredictionWe’re excited about the potential impact … Continue reading AI DIGEST #NOVEMBER20

KPMG IGNITION TOKYO、MLTとのパートナーシップを締結

KPMG Ignition Tokyoは、オープンエデュケーション、オープンソース、オープンサイエンスを通じた機械学習と人工知能の民主化に取り組む一般社団法人Machine Learning Tokyo とパートナーシップ契約を締結しました。MLTとのパートナーシップを通じて、テクノロジーコミュニティのさらなる成長と発展に貢献することを目指しています。

DLPOTW: DISCOVERING SYMBOLIC MODELS FROM DEEP LEARNING WITH INDUCTIVE BIASES

🚀 DEEP LEARNING PAPER OF THE WEEK Miles Cranmer, Alvaro Sanchez-Gonzalez, Peter Battaglia, Rui Xu, Kyle Cranmer, David Spergel, Shirley Ho Abstract "We develop a general approach to distill symbolic representations of a learned deep model by introducing strong inductive biases. We focus on Graph Neural Networks (GNNs). The technique works as follows: we first encourage sparse latent representations when we train … Continue reading DLPOTW: DISCOVERING SYMBOLIC MODELS FROM DEEP LEARNING WITH INDUCTIVE BIASES