What do you think of our Recurrent #NeuralNetworks based on dendritic computation?
For time series prediction with long horizons (tested on Lorenz #attractor and #epilepsy #EEG) it performs better than #LSTM and #GRU
link.springer.com/article/10.1...

Learning from Missing Values: Encoding Missingness in Representation-Space for LSTM Time Series F...

Jason Kemp, Stefan C. Kremer, Genevieve Ali, Daniel Gillis

Action editor: Ying Nian Wu

https://openreview.net/forum?id=DMmCMIrrez

#missingness #imputation #lstm

"LSTM" stands for "long short-term memory", the neural network architecture that predates the more parallel "transformer" architecture of current language models. Yet out of frustration with LLM output that has filled web search results, I first read it as "looks slop to me."

#lstm […]

“Evaluation of LSTM-Based Short-Term Prediction of MBR Operational Parameters: Applicability and Limitations for Aeration Control Applications”

#LSTM
#MBR
#process_monitoring

onlinelibrary.wiley.com/doi/10.1002/...

Automata Learning from Recurrent Networks: A Critical Synthesis for Verification, Testing, and In...

Jaouhar Slimi, Augustin Lemesle, Tristan Le Gall, Zakaria Chihani

Action editor: Blake Richards

https://openreview.net/forum?id=R52ETbUBVo

#lstm #rnns #automata

Quantification and Control of LSTM Resilience Based on Stability Theory

Sota Yoshihara, Ryosuke Yamamoto, Hiroyuki Kusumoto, Masanari Shimura

Action editor: John Timothy Halloran

https://openreview.net/forum?id=hFmlMUNEsR

#lstm #resilience #stability