2 papers
cs.LG2026
Seq2Synth: Benchmarking Temporal Fidelity in Synthetic Sequential Tabular Data
Kiwan Kwon, Kangmin Kim, Hojin Lee +5
Synthetic sequential tabular data are increasingly used for privacy-preserving data sharing and research, yet conventional tabular metrics often overlook temporal structure. Existi…
cs.LG2024
The SaTML '24 CNN Interpretability Competition: New Innovations for Concept-Level Interpretability
Stephen Casper, Jieun Yun, Joonhyuk Baek +13
Interpretability techniques are valuable for helping humans understand and oversee AI systems. The SaTML 2024 CNN Interpretability Competition solicited novel methods for studying…