Nicholas M. Boffi

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 26

Top Topics

Adaptive Control

Stochastic Gradient

Top Venues

Publications

Yifan Chen, Mark Goldstein, Mengjian Hua, Michael S. Albergo, Nicholas M. Boffi, Eric Vanden-Eijnden
Probabilistic Forecasting with Stochastic Interpolants and Föllmer Processes. CoRR (2024)
Nicholas M. Boffi, Michael S. Albergo, Eric Vanden-Eijnden
Flow Map Matching. CoRR (2024)
Nanye Ma, Mark Goldstein, Michael S. Albergo, Nicholas M. Boffi, Eric Vanden-Eijnden, Saining Xie
SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers. CoRR (2024)
Nicholas M. Boffi, Eric Vanden-Eijnden
Probability flow solution of the Fokker-Planck equation. Mach. Learn. Sci. Technol. 4 (3) (2023)
Michael S. Albergo, Nicholas M. Boffi, Eric Vanden-Eijnden
Stochastic Interpolants: A Unifying Framework for Flows and Diffusions. CoRR (2023)
Nicholas M. Boffi, Eric Vanden-Eijnden
Deep learning probability flows and entropy production rates in active matter. CoRR (2023)
Michael S. Albergo, Mark Goldstein, Nicholas M. Boffi, Rajesh Ranganath, Eric Vanden-Eijnden
Stochastic interpolants with data-dependent couplings. CoRR (2023)
Saminda Abeyruwan, Alex Bewley, Nicholas M. Boffi, Krzysztof Choromanski, David B. D'Ambrosio, Deepali Jain, Pannag Sanketi, Anish Shankar, Vikas Sindhwani, Sumeet Singh, Jean-Jacques E. Slotine, Stephen Tu
Agile Catching with Whole-Body MPC and Blackbox Policy Learning. CoRR (2023)
Michael S. Albergo, Nicholas M. Boffi, Michael Lindsey, Eric Vanden-Eijnden
Multimarginal generative modeling with stochastic interpolants. CoRR (2023)
Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine
Nonparametric adaptive control and prediction: theory and randomized algorithms. J. Mach. Learn. Res. 23 (2022)
Nicholas M. Boffi, Eric Vanden-Eijnden
Probability flow solution of the Fokker-Planck equation. CoRR (2022)
Thomas T. C. K. Zhang, Stephen Tu, Nicholas M. Boffi, Jean-Jacques E. Slotine, Nikolai Matni
Adversarially Robust Stability Certificates can be Sample-Efficient. L4DC (2022)
Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine
The role of optimization geometry in single neuron learning. AISTATS (2022)
Nicholas M. Boffi, Jean-Jacques E. Slotine
Implicit Regularization and Momentum Algorithms in Nonlinearly Parameterized Adaptive Control and Prediction. Neural Comput. 33 (3) (2021)
Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine
Nonparametric Adaptive Control and Prediction: Theory and Randomized Algorithms. CDC (2021)
Thomas T. C. K. Zhang, Stephen Tu, Nicholas M. Boffi, Jean-Jacques E. Slotine, Nikolai Matni
Adversarially Robust Stability Certificates can be Sample-Efficient. CoRR (2021)
Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine
Random features for adaptive nonlinear control and prediction. CoRR (2021)
Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine
Regret Bounds for Adaptive Nonlinear Control. L4DC (2021)
Nicholas M. Boffi, Jean-Jacques E. Slotine
A Continuous-Time Analysis of Distributed Stochastic Gradient. Neural Comput. 32 (1) (2020)
Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine
Regret Bounds for Adaptive Nonlinear Control. CoRR (2020)
Nicholas M. Boffi, Stephen Tu, Nikolai Matni, Jean-Jacques E. Slotine, Vikas Sindhwani
Learning Stability Certificates from Data. CoRL (2020)
Nicholas M. Boffi, Chris H. Rycroft
Parallel three-dimensional simulations of quasi-static elastoplastic solids. Comput. Phys. Commun. 257 (2020)
Nicholas M. Boffi, Jean-Jacques E. Slotine
The Reflectron: Exploiting geometry for learning generalized linear models. CoRR (2020)
Nicholas M. Boffi, Stephen Tu, Nikolai Matni, Jean-Jacques E. Slotine, Vikas Sindhwani
Learning Stability Certificates from Data. CoRR (2020)
Nicholas M. Boffi, Jean-Jacques E. Slotine
Higher-order algorithms for nonlinearly parameterized adaptive control. CoRR (2019)
Nicholas M. Boffi, Jean-Jacques E. Slotine
A continuous-time analysis of distributed stochastic gradient. CoRR (2018)