Scale-invariant temporal history (SITH): optimal slicing of the past in an uncertain world. - Tyler A. Spears; Brandon G. Jacques; Marc W. Howard; Per B. Sederberg (CoRR, 2017)

DeepSITH: Efficient Learning via Decomposition of What and When Across Time Scales. - Brandon G. Jacques; Zoran Tiganj; Marc W. Howard; Per B. Sederberg (NeurIPS, 2021)

SITHCon: A neural network robust to variations in input scaling on the time dimension. - Brandon G. Jacques; Zoran Tiganj; Aakash Sarkar; Marc W. Howard; Per B. Sederberg (CoRR, 2021)

A deep convolutional neural network that is invariant to time rescaling. - Brandon G. Jacques; Zoran Tiganj; Aakash Sarkar; Marc W. Howard; Per B. Sederberg (ICML, 2022)

Representing Latent Dimensions Using Compressed Number Lines. - Sahaj Singh Maini; James Mochizuki-Freeman; Chirag Shankar Indi; Brandon G. Jacques; Per B. Sederberg; Marc W. Howard; Zoran Tiganj (IJCNN, 2023)