Jean-jacques Bruna
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Computer Science
Jean-jacques Bruna's Degrees
- Bachelors Computer Science Stanford University
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(Suggest an Edit or Addition)Jean-jacques Bruna's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Intriguing properties of neural networks (2013) (10943)
- Spectral Networks and Locally Connected Networks on Graphs (2013) (3462)
- Geometric Deep Learning: Going beyond Euclidean data (2016) (2460)
- Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation (2014) (1448)
- Deep Convolutional Networks on Graph-Structured Data (2015) (1347)
- Invariant Scattering Convolution Networks (2012) (1131)
- Few-Shot Learning with Graph Neural Networks (2017) (925)
- Training Convolutional Networks with Noisy Labels (2014) (551)
- Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges (2021) (457)
- Video (language) modeling: a baseline for generative models of natural videos (2014) (419)
- Spectral Networks and Deep Locally Connected Networks on Graphs (2014) (297)
- Super-Resolution with Deep Convolutional Sufficient Statistics (2015) (293)
- Supervised Community Detection with Line Graph Neural Networks (2017) (228)
- Invariant Scattering Convolution Networks. (2012) (199)
- On the equivalence between graph isomorphism testing and function approximation with GNNs (2019) (190)
- Topology and Geometry of Half-Rectified Network Optimization (2016) (189)
- Can graph neural networks count substructures? (2020) (156)
- Stability Properties of Graph Neural Networks (2019) (140)
- Unsupervised Learning of Spatiotemporally Coherent Metrics (2014) (135)
- Classification with scattering operators (2010) (131)
- Deep Geometric Prior for Surface Reconstruction (2018) (131)
- Mathematics of Deep Learning (2017) (107)
- Surface Networks (2017) (87)
- A Note on Learning Algorithms for Quadratic Assignment with Graph Neural Networks (2017) (83)
- Kymatio: Scattering Transforms in Python (2018) (82)
- Signal recovery from Pooling Representations (2013) (82)
- A Mathematical Motivation for Complex-Valued Convolutional Networks (2015) (80)
- Diffusion Scattering Transforms on Graphs (2018) (79)
- Spurious Valleys in Two-layer Neural Network Optimization Landscapes (2018) (70)
- Pommerman: A Multi-Agent Playground (2018) (68)
- Graph Neural Networks for IceCube Signal Classification (2018) (63)
- Community Detection with Graph Neural Networks (2017) (63)
- Gradient Dynamics of Shallow Univariate ReLU Networks (2019) (63)
- Stability of Graph Scattering Transforms (2019) (62)
- Neural Networks with Finite Intrinsic Dimension have no Spurious Valleys (2018) (59)
- Neural Message Passing for Jet Physics (2017) (54)
- Intermittent process analysis with scattering moments (2013) (51)
- REVISED NOTE ON LEARNING QUADRATIC ASSIGNMENT WITH GRAPH NEURAL NETWORKS (2018) (50)
- On the Expressive Power of Deep Polynomial Neural Networks (2019) (49)
- Audio Texture Synthesis with Scattering Moments (2013) (44)
- Spurious Valleys in One-hidden-layer Neural Network Optimization Landscapes (2019) (44)
- Backplay: "Man muss immer umkehren" (2018) (42)
- Understanding Trainable Sparse Coding with Matrix Factorization (2016) (41)
- Learning Stable Group Invariant Representations with Convolutional Networks (2013) (39)
- Global convergence of neuron birth-death dynamics (2019) (37)
- Scattering Representations for Recognition (2013) (34)
- Unsupervised Feature Learning from Temporal Data (2015) (33)
- Multiscale sparse microcanonical models (2018) (30)
- Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias (2019) (28)
- A mean-field analysis of two-player zero-sum games (2020) (25)
- Extended Unconstrained Features Model for Exploring Deep Neural Collapse (2022) (21)
- A Permutation-Equivariant Neural Network Architecture For Auction Design (2020) (19)
- Topology and Geometry of Deep Rectified Network Optimization Landscapes (2016) (16)
- Neural Fields as Learnable Kernels for 3D Reconstruction (2021) (16)
- Blind Deconvolution with Non-local Sparsity Reweighting (2013) (15)
- Source separation with scattering Non-Negative Matrix Factorization (2015) (14)
- Neuron birth-death dynamics accelerates gradient descent and converges asymptotically (2019) (14)
- Divide and Conquer Networks (2016) (14)
- Blind Deconvolution with Re-weighted Sparsity Promotion (2013) (14)
- Pure and Spurious Critical Points: a Geometric Study of Linear Networks (2019) (14)
- Lattice-Based Methods Surpass Sum-of-Squares in Clustering (2021) (13)
- On the Sample Complexity of Learning with Geometric Stability (2021) (13)
- Advancing GraphSAGE with A Data-Driven Node Sampling (2019) (13)
- Neural Galerkin Scheme with Active Learning for High-Dimensional Evolution Equations (2022) (12)
- Probing the State of the Art: A Critical Look at Visual Representation Evaluation (2019) (12)
- Understanding Neural Sparse Coding with Matrix Factorization (2016) (12)
- Geometric Insights into the Convergence of Nonlinear TD Learning (2019) (12)
- Inverse Problems with Invariant Multiscale Statistics (2016) (11)
- Understanding the Learned Iterative Soft Thresholding Algorithm with matrix factorization (2017) (10)
- Approximating Orthogonal Matrices with Effective Givens Factorization (2019) (10)
- On the Cryptographic Hardness of Learning Single Periodic Neurons (2021) (10)
- A theoretical argument for complex-valued convolutional networks (2015) (9)
- Stability of Graph Neural Networks to Relative Perturbations (2019) (9)
- Classification with invariant scattering representations (2011) (8)
- Voice Conversion using Convolutional Neural Networks (2016) (8)
- An Extensible Benchmark Suite for Learning to Simulate Physical Systems (2021) (8)
- A Rate-Distortion Framework for Explaining Black-box Model Decisions (2021) (7)
- Supervised Community Detection with Hierarchical Graph Neural Networks (2017) (7)
- On the Expected Dynamics of Nonlinear TD Learning (2019) (6)
- Divide and Conquer with Neural Networks (2017) (5)
- Adaptive Acceleration of Sparse Coding via Matrix Factorization (2016) (5)
- METHODS FOR THE EVALUATION OF NEW POWER QUALITY PARAMETERS: A REVIEW OF RAPID VOLTAGE CHANGES AND SUPRAHARMONICS (2019) (4)
- Cartoon Explanations of Image Classifiers (2021) (4)
- On Feature Learning in Neural Networks with Global Convergence Guarantees (2022) (4)
- Audio Source Separation with Discriminative Scattering Networks (2014) (4)
- Scattering Representations for Recognition. (Representations en Scattering pour la Reconaissance) (2013) (3)
- Exponential Separations in Symmetric Neural Networks (2022) (3)
- Learning Single-Index Models with Shallow Neural Networks (2022) (3)
- Guest Editorial: Non-Euclidean Machine Learning (2022) (2)
- Provably Efficient Third-Person Imitation from Offline Observation (2020) (2)
- Dual Training of Energy-Based Models with Overparametrized Shallow Neural Networks (2021) (2)
- Simultaneous Transport Evolution for Minimax Equilibria on Measures (2022) (2)
- Telekia speciosa (Schreb.) Baumg. in human made environment: spread and persistence, two sides of the same coin (2020) (2)
- On Non-Linear operators for Geometric Deep Learning (2022) (1)
- Extra-gradient with player sampling for provable fast convergence in n-player games (2019) (1)
- Bandlets for HDTV Video Processing (2008) (1)
- On the Sample Complexity of Learning under Invariance and Geometric Stability (2021) (1)
- Novel Calibration systems for the dynamic and steady-state testing of digital instrument transformers (2021) (1)
- A Computer-Based IEC 61850 Sampled Values Analyzer for Parallel Power Quality Analysis (2022) (1)
- Geometric models with co-occurrence groups (2010) (1)
- An IEC 61850 Sampled Values-based Analyzer for Power Quality applications on Smart Substations (2021) (1)
- A Functional-Space Mean-Field Theory of Partially-Trained Three-Layer Neural Networks (2022) (1)
- Towards Antisymmetric Neural Ansatz Separation (2022) (1)
- Learning Dynamic Programming with Split-Merge Networks (2016) (0)
- Supplementary Material for Surface Networks (2018) (0)
- Variations physiologiques du sapeur-pompier au cours d'un exercice en ambiance chaude (2005) (0)
- A novel tool for voltage event characterization based on the Wavelet theory (2012) (0)
- SIMULATE PHYSICAL SYSTEMS (2021) (0)
- Seasonal effects of climate manipulation on microbial community structure and function in mountain soils (2021) (0)
- Planning with Arithmetic and Geometric Attributes (2018) (0)
- Global-Local Graph Neural Networks for Node-Classification (2022) (0)
- O C ] 1 4 M ay 2 01 9 Approximating Orthogonal Matrices with Effective Givens Factorization (2019) (0)
- Volumetric Meshes: a Neural Network-friendly representation for 3D shapes generative models, (2019) (0)
- Convolution Networks with Stable Invariants (0)
- On-site PQ Measurements in a Real DC Micro-grid (2022) (0)
- Complex-valued convolutional networks yield data-driven multiscale windowed spectra (2015) (0)
- Multi-fidelity Stability for Graph Representation Learning (2021) (0)
- Talk 1: Convolutional neural networks against the curse of dimensionality (2016) (0)
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