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/ Spring 2019 topics

Date Name Topic
Nov. 30 [None [None]
Dec. 3 Ari Independent Component Analysis
Jan. 9 Netanel Ofer Automated Analysis of Interneuron Axonal Tree Morphology and Activity Patterns
Jan. 18 Nidhi Dynamic Time Warping
Jan. 25 Ben Bandit problems
Feb. 8 David Autoencoders
Feb. 15 Rachit Older Deep Learning Methods

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
Nov. 2 Titipat AllenNLP library and a little bit of Pytorch
Nov. 9 Roozbeh Multiple Hypothesis Testing
Nov. 16 David Reinforcement learning and catastrophic forgetting

Previous lab teaching