← Authors

Joan Bruna

56 papers · 2014–2025 · 10 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (12) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (10) πŸƒ Academic Marathon (11) 🐝 Cross-Pollinator (8) 🏠 Conference Loyalist (22) πŸ”¬ Deep Specialist (13) πŸ‘‘ Triple Crown 🧬 Topic Evolution πŸ† Keyword Champion (3) πŸ† Grand Slam πŸ—ƒοΈ Keyword Collector (220) ⚑ Prolific Year (11) πŸš€ Conference Pioneer πŸ’Ž Century Club (56) πŸ”₯ Unstoppable (8) πŸ“ˆ Trend Setter ❓ The Questioner (2)

Conferences

NIPS (22) ICLR (10) ICML (10) CVPR (4) COLT (3) JMLR (3) AAAI (1) ECCV (1) ICCV (1) UAI (1)

Top co-authors

Zhengdao Chen (6) Denis Zorin (5) Aaron Zweig (5) Lei Chen (5) David Brandfonbrener (5) Samy Jelassi (5) Alberto Bietti (5) Eric Vanden-Eijnden (4) Matthew Trager (4) Francis Williams (4)

Research topics

Optimization (1)

Keywords

neural network (7) representation learning (5) graph neural network (4) gradient descent (4) neural network optimization (4) shallow neural network (3) single-index model (3) approximation theory (2) feature learning (2) low-degree polynomial (2) convolutional neural network (2) expressive power (2) behavior policy (2) offline reinforcement learning (2) neural collapse (2) nash equilibrium (2) imitation learning (2) surface reconstruction (2) high-dimensional regression (2) sample complexity (2)

Papers

Mean-field analysis of polynomial-width two-layer neural network beyond finite time horizon COLT 2025
Thermalizer: Stable autoregressive neural emulation of spatiotemporal chaos ICML 2025
Quality over Quantity in Attention Layers: When Adding More Heads Hurts ICLR 2025
Distributional Associations vs In-Context Reasoning: A Study of Feed-forward and Attention Layers ICLR 2025
Provable Posterior Sampling with Denoising Oracles via Tilted Transport NIPS 2024
Computational-Statistical Gaps in Gaussian Single-Index Models (Extended Abstract) COLT 2024
Stochastic Optimal Control Matching NIPS 2024
Symmetric Single Index Learning ICLR 2024
Beyond the Edge of Stability via Two-step Gradient Updates ICML 2023
Conditionally Strongly Log-Concave Generative Models ICML 2023
On Single-Index Models beyond Gaussian Data NIPS 2023
A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks NIPS 2023
Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation NIPS 2023
When does return-conditioned supervised learning work for offline reinforcement learning? NIPS 2022
Learning single-index models with shallow neural networks NIPS 2022
On Non-Linear operators for Geometric Deep Learning NIPS 2022
Exponential Separations in Symmetric Neural Networks NIPS 2022
Neural Fields As Learnable Kernels for 3D Reconstruction CVPR 2022
Cartoon Explanations of Image Classifiers ECCV 2022
On feature learning in neural networks with global convergence guarantees ICLR 2022
Depth separation beyond radial functions JMLR 2022
Extended Unconstrained Features Model for Exploring Deep Neural Collapse ICML 2022
Lattice-Based Methods Surpass Sum-of-Squares in Clustering COLT 2022
Neural Splines: Fitting 3D Surfaces With Infinitely-Wide Neural Networks CVPR 2021
Offline RL Without Off-Policy Evaluation NIPS 2021
On the Sample Complexity of Learning under Geometric Stability NIPS 2021
On the Cryptographic Hardness of Learning Single Periodic Neurons NIPS 2021
A Permutation-Equivariant Neural Network Architecture For Auction Design AAAI 2021
On Graph Neural Networks versus Graph-Augmented MLPs ICLR 2021
Offline Contextual Bandits with Overparameterized Models ICML 2021
On Energy-Based Models with Overparametrized Shallow Neural Networks ICML 2021
A Functional Perspective on Learning Symmetric Functions with Neural Networks ICML 2021
Pure and Spurious Critical Points: a Geometric Study of Linear Networks ICLR 2020
Extra-gradient with player sampling for faster convergence in n-player games ICML 2020
Kymatio: Scattering Transforms in Python JMLR 2020
A Dynamical Central Limit Theorem for Shallow Neural Networks NIPS 2020
Provably Efficient Third-Person Imitation from Offline Observation UAI 2020
IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method NIPS 2020
A mean-field analysis of two-player zero-sum games NIPS 2020
Can Graph Neural Networks Count Substructures? NIPS 2020
Geometric Insights into the Convergence of Nonlinear TD Learning ICLR 2020
Stability of Graph Scattering Transforms NIPS 2019
Deep Geometric Prior for Surface Reconstruction CVPR 2019
Gradient Dynamics of Shallow Univariate ReLU Networks NIPS 2019
Supervised Community Detection with Line Graph Neural Networks ICLR 2019
Diffusion Scattering Transforms on Graphs ICLR 2019
Spurious Valleys in One-hidden-layer Neural Network Optimization Landscapes JMLR 2019
Approximating Orthogonal Matrices with Effective Givens Factorization ICML 2019
Neuron birth-death dynamics accelerates gradient descent and converges asymptotically ICML 2019
Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias NIPS 2019
On the Expressive Power of Deep Polynomial Neural Networks NIPS 2019
On the equivalence between graph isomorphism testing and function approximation with GNNs NIPS 2019
Divide and Conquer Networks ICLR 2018
Surface Networks CVPR 2018
Unsupervised Learning of Spatiotemporally Coherent Metrics ICCV 2015
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation NIPS 2014