Likelihood-Free Frequentist Inference: Bridging Classical Statistics and Machine Learning for Reliable Simulator-Based Inference N Dalmasso, L Masserano, D Zhao, R Izbicki, AB Lee arXiv preprint arXiv:2107.03920, 2021 | 24* | 2021 |
Simulator-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems L Masserano, T Dorigo, R Izbicki, M Kuusela, AB Lee International Conference on Artificial Intelligence and Statistics (AISTATS), 2023 | 10* | 2023 |
Adaptive Sampling for Probabilistic Forecasting under Distribution Shift L Masserano, SS Rangapuram, S Kapoor, RS Nirwan, Y Park, ... NeurIPS 2022 Distribution Shifts Workshop, 2022 | 4 | 2022 |
Classification under Nuisance Parameters and Generalized Label Shift in Likelihood-Free Inference L Masserano, A Shen, M Doro, T Dorigo, R Izbicki, AB Lee International Conference of Machine Learning (ICML), 2024 | | 2024 |
End-To-End Optimization of the Layout of a Gamma Ray Observatory T Dorigo, M Aehle, J Donini, M Doro, NR Gauger, R Izbicki, A Lee, ... arXiv preprint arXiv:2310.01857, 2023 | | 2023 |
Likelihood-Free Frequentist Inference for Calorimetric Muon Energy Measurement in High-Energy Physics L Masserano, T Dorigo, R Izbicki, M Kuusela, AB Lee NeurIPS 2022 Machine Learning and the Physical Sciences Workshop, 2022 | | 2022 |