https://www.quantamagazine.org/how-ai-transformers-mimic-parts-of-the-brain-20220912/ How Transformers Seem to Mimic Parts of the BrainStephen OrnesSeptember 12, 2022 “Neural networks originally designed for language processing turn out to be great models of how our brains
What I Read: Causal Inference
https://thegradient.pub/causal-inference-connecting-data-and-reality/ Causal Inference: Connecting Data and RealityWenwen Ding04.Sep.2022 “Causal inference is a theory that describes, discriminates, and measures causal relationships, developed from statistics.”
What I Read: Beyond Message Passing, Graph Neural Networks
https://thegradient.pub/graph-neural-networks-beyond-message-passing-and-weisfeiler-lehman/ Beyond Message Passing: a Physics-Inspired Paradigm for Graph Neural NetworksMichael Bronstein07.May.2022 “…the “node and edge-centric” mindset of current graph deep learning schemes imposes strong limitations… we propose physics-inspired “continuous”
What I Read: Will Transformers Take Over Artificial Intelligence?
https://www.quantamagazine.org/will-transformers-take-over-artificial-intelligence-20220310/ Will Transformers Take Over Artificial Intelligence?A simple algorithm that revolutionized how neural networks approach language is now taking on vision as well. It may not stop there.Stephen OrnesContributing WriterMarch
What I Read: Interpretable Time Series
https://ai.googleblog.com/2021/12/interpretable-deep-learning-for-time.html Interpretable Deep Learning for Time Series ForecastingMonday, December 13, 2021Posted by Sercan O. Arik, Research Scientist and Tomas Pfister, Engineering Manager, Google Cloud “Multi-horizon forecasting, i.e. predicting variables-of-interest at