Joan Bruna

Courant Institute of Mathematical Sciences — United States

Computer Science · Physical Sciences

36h-index21.6kcitations192works0.32yr avg
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Research Topics

Neural Networks and Applications(29), Model Reduction and Neural Networks(26), Stochastic Gradient Optimization Techniques(25), Machine Learning and Algorithms(25), Advanced Graph Neural Networks(23)

Publications192 total

Generative Modeling from Black-box Corruptions via Self-Consistent Stochastic Interpolants
arXiv (Cornell University)·2025Open Access
Data-driven multiscale modeling for correcting dynamical systems
Machine Learning Science and Technology·2025Open Access
Emergence of Linear Truth Encodings in Language Models
arXiv (Cornell University)·2025Open Access
Axial Neural Networks for Dimension-Free Foundation Models
arXiv (Cornell University)·2025Open Access
Survey on Algorithms for Multi-Index Models
Statistical Science·2025
On learning Gaussian multi‐index models with gradient flow part I: General properties and two‐timescale learning
Communications on Pure and Applied Mathematics·2025
The Generative Leap: Sharp Sample Complexity for Efficiently Learning Gaussian Multi-Index Models
arXiv (Cornell University)·2025Open Access
Propagation of Chaos in One-hidden-layer Neural Networks beyond Logarithmic Time
arXiv (Cornell University)·2025Open Access
Survey on Algorithms for multi-index models
arXiv (Cornell University)·2025Open Access
Compositional Reasoning with Transformers, RNNs, and Chain of Thought
arXiv (Cornell University)·2025Open Access
Learning Machine Learning with Lorenz-96
Journal of Open Source Education·2024· 1 citedOpen Access
Posterior Sampling with Denoising Oracles via Tilted Transport
arXiv (Cornell University)·2024· 3 citedOpen Access
Distributional Associations vs In-Context Reasoning: A Study of Feed-forward and Attention Layers
arXiv (Cornell University)·2024Open Access
Computational-Statistical Gaps in Gaussian Single-Index Models
arXiv (Cornell University)·2024Open Access
Provable Posterior Sampling with Denoising Oracles via Tilted Transport
2024· 1 cited
Stochastic Optimal Control Matching
2024
Learning Machine Learning with Lorenz-96
2023Open Access
Stochastic Optimal Control Matching
arXiv (Cornell University)·2023Open Access
On Learning Gaussian Multi-index Models with Gradient Flow
arXiv (Cornell University)·2023Open Access
Neural Galerkin schemes with active learning for high-dimensional evolution equations
Journal of Computational Physics·2023· 33 cited
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Frequent Co-authors

Yann LeCun(10), Arthur Szlam(5), Stéphane Mallat(5), Zhengdao Chen(5), Soledad Villar(5), Wojciech Zaremba(4), Rob Fergus(4), Michael M. Bronstein(4), Fernando Gama(4), Alejandro Ribeiro(4), Afonso S. Bandeira(4), Denis Zorin(4), Daniele Panozzo(3), Emily Denton(2), Taco Cohen(2), Ross Goroshin(2), Jonathan Tompson(2), David Eigen(2), Xiang Li(2), Lei Chen(2)