TSMixer: An all-MLP Architecture for Time Series Forecast-ing
#forecasting #forecast #perceptrons
Transformer for Partial Differential Equations’ Operator Learning
Zijie Li, Kazem Meidani, Amir Barati Farimani
Action editor: Tie-Yan Liu.
#attention #perceptrons #convolutional
Modern researchers and practitioners of #NeuralNetworks should read the classic book "#Perceptrons: An Introduction to Computational Geometry" (1969) by Minsky and Papert, because every proponent should know the main arguments of the detractors.
https://en.wikipedia.org/wiki/Perceptrons_(book)
Transformer for Partial Differential Equations’ Operator Learning
#attention #perceptrons #convolutional
“We’re not on the brink of major technological development here. We’re in the middle of some fiddling at the edges of what came before… Just like the algorithms, we’re stuck repeating the aesthetics…” —Caleb Gamman in “Algorithms”
#AI #algorithms #algorithm #ArtificialIntelligence #perceptrons #NeuralNetworks #NeuralNetworks #AIWinter #Tesla
#ai #algorithms #algorithm #artificialintelligence #perceptrons #neuralnetworks #AIWinter #tesla