Systematically differentiating parametric discontinuities SP Bangaru, J Michel, K Mu, G Bernstein, TM Li, J Ragan-Kelley ACM Transactions on Graphics (TOG) 40 (4), 1-18, 2021 | 37 | 2021 |
𝜆ₛ: computable semantics for differentiable programming with higher-order functions and datatypes B Sherman, J Michel, M Carbin Proceedings of the ACM on Programming Languages 5 (POPL), 1-31, 2021 | 21 | 2021 |
Sound and robust solid modeling via exact real arithmetic and continuity B Sherman, J Michel, M Carbin Proceedings of the ACM on Programming Languages 3 (ICFP), 1-29, 2019 | 10 | 2019 |
Directed random geometric graphs J Michel, S Reddy, R Shah, S Silwal, R Movassagh Journal of Complex Networks 7 (5), 792-816, 2019 | 7 | 2019 |
A Theory of Equivalence-Preserving Program Embeddings L Weber, J Michel, A Renda, S Amarasinghe, M Carbin | 1 | 2022 |
Distributions for Compositionally Differentiating Parametric Discontinuities J Michel, K Mu, X Yang, SP Bangaru, ER Collins, G Bernstein, ... Proceedings of the ACM on Programming Languages 8 (OOPSLA1), 893-922, 2024 | | 2024 |
Sensitivities for guiding refinement in arbitrary-precision arithmetic J Michel Massachusetts Institute of Technology, 2020 | | 2020 |
NAP: Noise-Based Sensitivity Analysis for Programs J Michel, S Verma, B Sherman, M Carbin | | |
Machine Learning Reveals Pan-Cancer Biomarker J Michel | | |