| Stochastic interpolants: A unifying framework for flows and diffusions MS Albergo*, NM Boffi*, E Vanden-Eijnden arXiv preprint arXiv:2303.08797, 2023 | 234 | 2023 |
| Sit: Exploring flow and diffusion-based generative models with scalable interpolant transformers N Ma, M Goldstein, MS Albergo, NM Boffi, E Vanden-Eijnden, S Xie European Conference on Computer Vision, 23-40, 2024 | 111 | 2024 |
| Learning stability certificates from data N Boffi, S Tu, N Matni, JJ Slotine, V Sindhwani Conference on Robot Learning, 1341-1350, 2021 | 99 | 2021 |
| Implicit regularization and momentum algorithms in nonlinearly parameterized adaptive control and prediction NM Boffi, JJE Slotine Neural Computation 33 (3), 590-673, 2021 | 66* | 2021 |
| Regret bounds for adaptive nonlinear control NM Boffi, S Tu, JJE Slotine Learning for Dynamics and Control, 471-483, 2021 | 60 | 2021 |
| Probability flow solution of the fokker–planck equation NM Boffi, E Vanden-Eijnden Machine Learning: Science and Technology 4 (3), 035012, 2023 | 42 | 2023 |
| Efficient computation of the hartree–fock exchange in real-space with projection operators NM Boffi, M Jain, A Natan Journal of Chemical Theory and Computation 12 (8), 3614-3622, 2016 | 26 | 2016 |
| Nonparametric adaptive control and prediction: theory and randomized algorithms NM Boffi, S Tu, JJE Slotine Journal of Machine Learning Research, 1-46, 2022 | 24 | 2022 |
| Manifold learning for coarse-graining atomistic simulations: Application to amorphous solids K Kontolati, D Alix-Williams, NM Boffi, ML Falk, CH Rycroft, MD Shields Acta Materialia 215, 117008, 2021 | 19 | 2021 |
| Stochastic interpolants with data-dependent couplings MS Albergo, M Goldstein, NM Boffi, R Ranganath, E Vanden-Eijnden arXiv preprint arXiv:2310.03725, 2023 | 18 | 2023 |
| Deep learning probability flows and entropy production rates in active matter NM Boffi, E Vanden-Eijnden Proceedings of the National Academy of Sciences 121 (25), e2318106121, 2024 | 17 | 2024 |
| A continuous-time analysis of distributed stochastic gradient NM Boffi, JJE Slotine Neural computation 32 (1), 36-96, 2020 | 17 | 2020 |
| Probabilistic Forecasting with Stochastic Interpolants and Föllmer Processes Y Chen, M Goldstein, M Hua, MS Albergo, NM Boffi, E Vanden-Eijnden arXiv preprint arXiv:2403.13724, 2024 | 11 | 2024 |
| Characterizing the inverses of block tridiagonal, block Toeplitz matrices NM Boffi, JC Hill, MG Reuter Computational Science & Discovery 8 (1), 015001, 2014 | 10 | 2014 |
| Parallel three-dimensional simulations of quasi-static elastoplastic solids NM Boffi, CH Rycroft Computer Physics Communications 257, 107254, 2020 | 9* | 2020 |
| The role of dimensionality in the decay of surface effects MG Reuter, NM Boffi, MA Ratner, T Seideman The Journal of Chemical Physics 138 (8), 2013 | 9 | 2013 |
| Adversarially robust stability certificates can be sample-efficient T Zhang, S Tu, N Boffi, JJ Slotine, N Matni Learning for Dynamics and Control Conference, 532-545, 2022 | 7 | 2022 |
| Multimarginal generative modeling with stochastic interpolants MS Albergo, NM Boffi, M Lindsey, E Vanden-Eijnden arXiv preprint arXiv:2310.03695, 2023 | 6 | 2023 |
| Asymptotic behavior and interpretation of virtual states: The effects of confinement and of basis sets NM Boffi, M Jain, A Natan The Journal of Chemical Physics 144 (8), 2016 | 6 | 2016 |
| Agile Catching with Whole-Body MPC and Blackbox Policy Learning S Abeyruwan, A Bewley, NM Boffi, KM Choromanski, DB D’Ambrosio, ... Learning for Dynamics and Control Conference, 851-863, 2023 | 4 | 2023 |
Jean-Jacques SlotineMIT, Professor of Mechanical Engineering and Information Sciences, Professor of Brain SciencesZweryfikowany adres z mit.edu