Nicolas Boullé

55 papers A* 6Journal 49

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Generalized Discrete Diffusion from Snapshots. CoRR Oussama Zekri, Théo Uscidda, Nicolas Boullé, Anna Korba
2026	J	`jnl`	Jacobian Scopes: token-level causal attributions in LLMs. CoRR Toni J. B. Liu, Baran Zadeoglu, Nicolas Boullé, Raphaël Sarfati, Christopher J. Earls
2026	J	`jnl`	Trustworthy Koopman Operator Learning: Invariance Diagnostics and Error Bounds. CoRR Gustav Conradie, Nicolas Boullé, Jean-Christophe Loiseau, Steven L. Brunton, Matthew J. Colbrook
2025	J	`jnl`	Convergent Methods for Koopman Operators on Reproducing Kernel Hilbert Spaces. CoRR Nicolas Boullé, Matthew J. Colbrook, Gustav Conradie
2025	A*	`conf`	Density estimation with LLMs: a geometric investigation of in-context learning trajectories. ICLR Toni J. B. Liu, Nicolas Boullé, Raphaël Sarfati, Christopher J. Earls
2025	J	`jnl`	Fine-Tuning Discrete Diffusion Models with Policy Gradient Methods. CoRR Oussama Zekri, Nicolas Boullé
2025	A*	`conf`	Lines of Thought in Large Language Models. ICLR Raphaël Sarfati, Toni J. B. Liu, Nicolas Boullé, Christopher J. Earls
2025	J	`jnl`	Multi-Level Monte Carlo Training of Neural Operators. CoRR James Rowbottom, Stefania Fresca, Pietro Lio, Carola-Bibiane Schönlieb, Nicolas Boullé
2025	J	`jnl`	Multiplicative Dynamic Mode Decomposition. SIAM J. Appl. Dyn. Syst. Nicolas Boullé, Matthew J. Colbrook
2025	J	`jnl`	Randomized Nyström Approximation of Non-negative Self-Adjoint Operators. SIAM J. Math. Data Sci. David Persson, Nicolas Boullé, Daniel Kressner
2025	J	`jnl`	Text-Trained LLMs Can Zero-Shot Extrapolate PDE Dynamics. CoRR Jiajun Bao, Nicolas Boullé, Toni J. B. Liu, Raphaël Sarfati, Christopher J. Earls
2025	A*	`conf`	What's in a prompt? Language models encode literary style in prompt embeddings. EMNLP Raphaël Sarfati, Haley Moller, Toni J. B. Liu, Nicolas Boullé, Christopher J. Earls
2025	J	`jnl`	What's in a prompt? Language models encode literary style in prompt embeddings. CoRR Raphaël Sarfati, Haley Moller, Toni J. B. Liu, Nicolas Boullé, Christopher J. Earls
2024	J	`jnl`	Density estimation with LLMs: a geometric investigation of in-context learning trajectories. CoRR Toni J. B. Liu, Nicolas Boullé, Raphaël Sarfati, Christopher J. Earls
2024	A*	`conf`	LLMs learn governing principles of dynamical systems, revealing an in-context neural scaling law. EMNLP Toni J. B. Liu, Nicolas Boullé, Raphaël Sarfati, Christopher J. Earls
2024	J	`jnl`	LLMs learn governing principles of dynamical systems, revealing an in-context neural scaling law. CoRR Toni J. B. Liu, Nicolas Boullé, Raphaël Sarfati, Christopher J. Earls
2024	J	`jnl`	Large Language Models as Markov Chains. CoRR Oussama Zekri, Ambroise Odonnat, Abdelhakim Benechehab, Linus Bleistein, Nicolas Boullé, Ievgen Redko
2024	J	`jnl`	Lines of Thought in Large Language Models. CoRR Raphaël Sarfati, Toni J. B. Liu, Nicolas Boullé, Christopher J. Earls
2024	J	`jnl`	Multiplicative Dynamic Mode Decomposition. CoRR Nicolas Boullé, Matthew J. Colbrook
2024	J	`jnl`	Multivariate Rational Approximation of Functions with Curves of Singularities. SIAM J. Sci. Comput. Nicolas Boullé, Astrid Herremans, Daan Huybrechs
2024	J	`jnl`	On the Convergence of Hermitian Dynamic Mode Decomposition. CoRR Nicolas Boullé, Matthew J. Colbrook
2024	J	`jnl`	Operator learning regularization for macroscopic permeability prediction in dual-scale flow problem. CoRR Christina Runkel, Sinan Xiao, Nicolas Boullé, Yang Chen
2024	J	`jnl`	Operator learning without the adjoint. CoRR Nicolas Boullé, Diana Halikias, Samuel E. Otto, Alex Townsend
2024	J	`jnl`	Operator learning without the adjoint. J. Mach. Learn. Res. Nicolas Boullé, Diana Halikias, Samuel E. Otto, Alex Townsend
2024	J	`jnl`	Randomized Nyström approximation of non-negative self-adjoint operators. CoRR David Persson, Nicolas Boullé, Daniel Kressner
2024	J	`jnl`	Structure-Preserving Operator Learning. CoRR Nacime Bouziani, Nicolas Boullé
2023	J	`jnl`	A Mathematical Guide to Operator Learning. CoRR Nicolas Boullé, Alex Townsend
2023	J	`jnl`	Elliptic PDE learning is provably data-efficient. CoRR Nicolas Boullé, Diana Halikias, Alex Townsend
2023	J	`jnl`	Learning Elliptic Partial Differential Equations with Randomized Linear Algebra. Found. Comput. Math. Nicolas Boullé, Alex Townsend
2023	J	`jnl`	Multivariate rational approximation of functions with curves of singularities. CoRR Nicolas Boullé, Astrid Herremans, Daan Huybrechs
2023	J	`jnl`	Optimization of Hopf Bifurcation Points. SIAM J. Sci. Comput. Nicolas Boullé, Patrick E. Farrell, Marie E. Rognes
2022	A*	`conf`	A generalization of the randomized singular value decomposition. ICLR Nicolas Boullé, Alex Townsend
2022	J	`jnl`	Bifurcation analysis of a two-dimensional magnetic Rayleigh-Bénard problem. CoRR Fabian Laakmann, Nicolas Boullé
2022	J	`jnl`	Control of Bifurcation Structures using Shape Optimization. SIAM J. Sci. Comput. Nicolas Boullé, Patrick E. Farrell, Alberto Paganini
2022	J	`jnl`	Data-driven discovery of Green's functions. CoRR Nicolas Boullé
2022	J	`jnl`	Learning Green's functions associated with parabolic partial differential equations. CoRR Nicolas Boullé, Seick Kim, Tianyi Shi, Alex Townsend
2022	J	`jnl`	Learning Green's functions associated with time-dependent partial differential equations. J. Mach. Learn. Res. Nicolas Boullé, Seick Kim, Tianyi Shi, Alex Townsend
2022	J	`jnl`	Optimal control of Hopf bifurcations. CoRR Nicolas Boullé, Patrick E. Farrell, Marie E. Rognes
2022	J	`jnl`	Principled interpolation of Green's functions learned from data. CoRR Harshwardhan Praveen, Nicolas Boullé, Christopher J. Earls
2022	J	`jnl`	Two-Component 3D Atomic Bose-Einstein Condensates Support Complex Stable Patterns. CoRR Nicolas Boullé, I. Newell, Patrick E. Farrell, Panayotis G. Kevrekidis
2021	J	`jnl`	A generalization of the randomized singular value decomposition. CoRR Nicolas Boullé, Alex Townsend
2021	J	`jnl`	Accurate numerical simulation of electrodiffusion and water movement in brain tissue. CoRR Ada J. Ellingsrud, Nicolas Boullé, Patrick E. Farrell, Marie E. Rognes
2021	J	`jnl`	An optimal complexity spectral method for Navier-Stokes simulations in the ball. CoRR Nicolas Boullé, Jonasz Slomka, Alex Townsend
2021	J	`jnl`	Bifurcation analysis of two-dimensional Rayleigh-Bénard convection using deflation. CoRR Nicolas Boullé, Vassilios Dallas, Patrick E. Farrell
2021	J	`jnl`	Control of bifurcation structures using shape optimization. CoRR Nicolas Boullé, Patrick E. Farrell, Alberto Paganini
2021	J	`jnl`	Data-driven discovery of physical laws with human-understandable deep learning. CoRR Nicolas Boullé, Christopher J. Earls, Alex Townsend
2021	J	`jnl`	Learning elliptic partial differential equations with randomized linear algebra. CoRR Nicolas Boullé, Alex Townsend
2020	J	`jnl`	Bifurcation analysis of stationary solutions of two-dimensional coupled Gross-Pitaevskii equations using deflated continuation. Commun. Nonlinear Sci. Numer. Simul. Efstathios G. Charalampidis, Nicolas Boullé, Patrick E. Farrell, Panayotis G. Kevrekidis
2020	J	`jnl`	Computing with Functions in the Ball. SIAM J. Sci. Comput. Nicolas Boullé, Alex Townsend
2020	J	`jnl`	Deflation-based Identification of Nonlinear Excitations of the 3D Gross-Pitaevskii equation. CoRR Nicolas Boullé, Efstathios G. Charalampidis, Patrick E. Farrell, Panayotis G. Kevrekidis
2020	A*	`conf`	Rational neural networks. NeurIPS Nicolas Boullé, Yuji Nakatsukasa, Alex Townsend
2020	J	`jnl`	Rational neural networks. CoRR Nicolas Boullé, Yuji Nakatsukasa, Alex Townsend
2019	J	`jnl`	Bifurcation analysis of stationary solutions of two-dimensional coupled Gross-Pitaevskii equations using deflated continuation. CoRR Efstathios G. Charalampidis, Nicolas Boullé, Patrick E. Farrell, P. G. Kevrekidis
2019	J	`jnl`	Classification of chaotic time series with deep learning. CoRR Nicolas Boullé, Vassilios Dallas, Yuji Nakatsukasa, D. Samaddar
2019	J	`jnl`	Computing with functions in the ball. CoRR Nicolas Boullé, Alex Townsend