Safety, alignment & interpretability· 2015
Understanding Neural Networks Through Deep Visualization
On the reading lists
- #57 in Safety, alignment & interpretability (2026 edition)
Why it matters
Early systematic visualization tools for neural nets.
Condensed from the expert lists' notes.
The record
- First released
- 2015 (from arXiv 1506.06579)
- Citations
- 1,981 citations, as counted by
Semantic Scholar (non-commercial licence) - Named by
- both expert lists
- Score
- 0.311 · computed rank 578 · consensus 0.275, must-read 0, citations percentile 0.511 (2010s · safety), awards 0, existing lists 0.5. Method
Data sources
Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0), and
Semantic Scholar (used under its non-commercial API licence). Each count names its source. See the method.