Selective Classification for Deep Neural Networks. - Yonatan Geifman; Ran El-Yaniv (NIPS, 2017)

The Prediction Advantage: A Universally Meaningful Performance Measure for Classification and Regression. - Ran El-Yaniv; Yonatan Geifman; Yair Wiener (CoRR, 2017)

Deep Active Learning over the Long Tail. - Yonatan Geifman; Ran El-Yaniv (CoRR, 2017)

Boosting Uncertainty Estimation for Deep Neural Classifiers. - Yonatan Geifman; Guy Uziel; Ran El-Yaniv (CoRR, 2018)

Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers. - Yonatan Geifman; Guy Uziel; Ran El-Yaniv (ICLR (Poster), 2019)

SelectiveNet: A Deep Neural Network with an Integrated Reject Option. - Yonatan Geifman; Ran El-Yaniv (ICML, 2019)

Deep Active Learning with a Neural Architecture Search. - Yonatan Geifman; Ran El-Yaniv (NeurIPS, 2019)

Distribution Shift Detection for Deep Neural Networks. - Guy Bar-Shalom; Yonatan Geifman; Ran El-Yaniv (CoRR, 2022)

Window-Based Distribution Shift Detection for Deep Neural Networks. - Guy Bar-Shalom; Yonatan Geifman; Ran El-Yaniv (NeurIPS, 2023)

Puzzle: Distillation-Based NAS for Inference-Optimized LLMs. - Akhiad Bercovich; Tomer Ronen; Talor Abramovich; Nir Ailon; Nave Assaf; Mohammad Dabbah; Ido Galil; Amnon Geifman; Yonatan Geifman; Izhak Golan; Netanel Haber; Ehud Karpas; et al. (CoRR, 2024)

FFN Fusion: Rethinking Sequential Computation in Large Language Models. - Akhiad Bercovich; Mohammad Dabbah; Omri Puny; Ido Galil; Amnon Geifman; Yonatan Geifman; Izhak Golan; Ehud Karpas; Itay Levy; Zach Moshe; Najeeb Nabwani; Tomer Ronen; et al. (CoRR, 2025)