Upcoming lab teachings
posted on August 29, 2018

Upcoming lab teachings

Every Friday, we get together (over pizza, sometimes) for lab teachings. On a rotating basis, each member of the lab speaks and teaches about something they know. Anything, really. Relevant and interesting topics, good skills to know, nice Python packages, neuroscientific princples, new findings and literature reviews… whatever!

Fall 2018 topics

Date Name Topic
Nov. 2 Titipat AllenNLP library and a little bit of Pytorch
Nov. 9 Roozbeh Multiple Hypothesis Testing
Nov. 16 David TBD
Nov. 30 Brianna T.B.D. (maybe decoding/electrophys related)
Dec. 3 Ari Independent Component Analysis

Requests and suggestions

  1. Recent progress in NLP (Transformer networks, pretraining methods…)
  2. Graph Convolution Technique

Recently taught topics

For inspiration. Add ones you’ve done!!

  1. Generalization in neural networks (Ari)
  2. Synaptic learning rules (Ari)
  3. How to science (debugging strategies etc.) (Konrad)
  4. Reinforcement learning and causal inference (Ben)
  5. DAGs and causal inference (Ben)
  6. Neuron firing dynamics and bifurcations(Ilenna)
  7. Submodular functions (Roozbeh)
  8. Recommendation systems (Rachit)
Sept. 28: Ilenna Capacity of Neural Networks
Oct. 5: Tung Pham GANs for EEG
Oct. 12: Ben GPUs – beneath the heatsink Slides
Oct. 19: Rachit Graph Convolution Networks
Oct. 26: Tony Docker for science

Previous lab teaching