Slides

• The neural architecture of language: Integrative modeling converges on predictive processing. 2021-03-09, MIT BCS Saxe Lab
  [pdf]
• Program for Software Engineering, Guest Lecture: Engineering an Artificial Biological Intelligence. 2021-01-15, UNA/TUM, LMU
  [pdf]
• CBMM Panel Discussion: Should models of cortex be falsifiable? 2020-12-07, MIT (with Tomaso Poggio, Gabriel Kreiman, Josh McDermott, Leyla Isik, Susan Epstein, Jenelle Feather)
  [video]
• The neural architecture of language: Integrative modeling converges on predictive processing. 2020-12-01, France NLP GDR TAL
  [pdf]
• Integrative Benchmarking to Advance Neural Models of Vision and Language. 2020-11-25, Virtual Computational Neuroscience Journal Club
  [pdf, recording]
• Integrative Benchmarking and the Value of Quantitative Models. 2020-10-19, CCN GAC linear/nonlinear workshop
  [pdf]
• Wiring Up Vision: Minimizing Supervised Synaptic Updates Needed to Produce a Primate Ventral Stream. 2020-10-06, C-BRIC Annual Review
  [pdf]
• Artificial Neural Networks Accurately Predict Language Processing in the Brain. 2020-08-18, MIT BCS Cog Lunch
  [pdf, code]
• Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs. 2020-03-31, neuromatch.io contributed talk
  [pdf, video (starts at 22:45)]
• Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs. 2019-12-12, NeurIPS Oral
  [talk recording, slides pdf, slides powerpoint, poster pdf, code, 3min-video]
• Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs. 2019-10-29, MIT BCS Cog Lunch
  [pdf]
• Deep Networks and Pytorch. 2019-08-21, Harvard-MIT Computational Neuroscience Journal Club
  [notebook, github]
• Continual Learning with Self-Organizing Maps. 2018-12-07, NeurIPS Continual Learning Workshop
  [poster pdf]
• Aligning Deep Neural Networks and Visual Cortex. 2018-03-01, MIT IQ Launch
  [pdf, powerpoint]
• A Flexible Approach to Automated RNN Architecture Generation. 2018-02-14, Tenenbaum lab
  [pdf, powerpoint]
• Introduction to Deep Learning for Neuroscientists. 2017-10-27, MIT BCS Peer Lectures
  [powerpoint, pdf]
• Recurrent computations for pattern completion. 2016-20-10, Harvard Systems Club
  [pdf]