Been Kim
where else to find them
no profile links on file
what they talk about
where they keep going back
no series more than once — all 3 in the filters
on a stage with
never shared a talk
who talks about the same things
nobody close enough yet
| title | conference | date |
|---|---|---|
| Interpretability For Everyone | Women in Data Science (WiDS) Stanford 2020 | 2020-03-02 |
Shows that saliency maps fail sanity checks by barely changing even after networks are randomized, so visual explanations can be misleading; develops TCAV… | ||
| How to Fail Interpretability Research | Emerging Challenges in Deep Learning (Simons Institute workshop, 2019) | 2019-08-05 |
Field surveys identify 11 recurring ways research stalls and offer concrete checks and datasets to avoid them, for example a synthetic attribution test that… | ||
| Interpretability - now what? | Frontiers of Deep Learning 2019 | 2019-07-15 |
Shows that common saliency maps barely change when network weights are randomized and fail simple sanity checks, so a benchmark with controlled object… | ||
| nothing matches | ||