Session 1


Monday, 6th April

Chairman: Kofi Makinwa

Analog Circuits for Machine Learning

  1. Navigating the Hype – A Machine Learning Primer for Circuit Designers – Boris Murmann (Stanford)
  2. Mixed-signal compute and memory fabrics for deep neural networks –  Boris Murmann (Stanford)
  3. Analog RRAM for computation and supporting circuits – Mike Flynn (University of Mich)
  4. Analog circuits for deep learning networks – Shih-Chii Liu (UZH and ETHZ)
  5. SPIRIT: a mixed-signal SNN with co-integrated CMOS neurons and resistive synapses – François Rummens (LETI)
  6. Accelerated neuromorphic computing – Johannes Schemmel (University of Heidelberg)

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