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Nicholas M. Boffi
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Cited by
Year
Stochastic interpolants: A unifying framework for flows and diffusions
MS Albergo*, NM Boffi*, E Vanden-Eijnden
arXiv preprint arXiv:2303.08797, 2023
1812023
Learning stability certificates from data
N Boffi, S Tu, N Matni, JJ Slotine, V Sindhwani
Conference on Robot Learning, 1341-1350, 2021
962021
Implicit regularization and momentum algorithms in nonlinearly parameterized adaptive control and prediction
NM Boffi, JJE Slotine
Neural Computation 33 (3), 590-673, 2021
63*2021
Regret bounds for adaptive nonlinear control
NM Boffi, S Tu, JJE Slotine
Learning for Dynamics and Control, 471-483, 2021
582021
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
arXiv preprint arXiv:2401.08740, 2024
522024
Probability flow solution of the fokker–planck equation
NM Boffi, E Vanden-Eijnden
Machine Learning: Science and Technology 4 (3), 035012, 2023
342023
Nonparametric adaptive control and prediction: theory and randomized algorithms
NM Boffi, S Tu, JJE Slotine
Journal of Machine Learning Research, 1-46, 2022
252022
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
252016
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
182021
Stochastic interpolants with data-dependent couplings
MS Albergo, M Goldstein, NM Boffi, R Ranganath, E Vanden-Eijnden
arXiv preprint arXiv:2310.03725, 2023
152023
A continuous-time analysis of distributed stochastic gradient
NM Boffi, JJE Slotine
Neural computation 32 (1), 36-96, 2020
142020
Characterizing the inverses of block tridiagonal, block Toeplitz matrices
NM Boffi, JC Hill, MG Reuter
Computational Science & Discovery 8 (1), 015001, 2014
102014
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
92013
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
82024
Parallel three-dimensional simulations of quasi-static elastoplastic solids
NM Boffi, CH Rycroft
Computer Physics Communications 257, 107254, 2020
8*2020
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
72022
Stochastic interpolants: A unifying framework for flows and diffusions, 2023
MS Albergo, NM Boffi, E Vanden-Eijnden
ArXiv preprint ArXiv230308797, 0
7
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
62024
Multimarginal generative modeling with stochastic interpolants
MS Albergo, NM Boffi, M Lindsey, E Vanden-Eijnden
arXiv preprint arXiv:2310.03695, 2023
62023
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
62016
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