March 19, 2024, 4:45 a.m. | Aaron Spieler, Nasim Rahaman, Georg Martius, Bernhard Sch\"olkopf, Anna Levina

cs.LG updates on arXiv.org arxiv.org

arXiv:2306.16922v3 Announce Type: replace-cross
Abstract: Biological cortical neurons are remarkably sophisticated computational devices, temporally integrating their vast synaptic input over an intricate dendritic tree, subject to complex, nonlinearly interacting internal biological processes. A recent study proposed to characterize this complexity by fitting accurate surrogate models to replicate the input-output relationship of a detailed biophysical cortical pyramidal neuron model and discovered it needed temporal convolutional networks (TCN) with millions of parameters. Requiring these many parameters, however, could stem from a misalignment …

abstract arxiv complexity computational cs.ai cs.lg cs.ne devices horizon memory neuron neurons processes q-bio.nc solve study tasks tree type vast

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Business Data Scientist, gTech Ads

@ Google | Mexico City, CDMX, Mexico

Lead, Data Analytics Operations

@ Zocdoc | Pune, Maharashtra, India