Guy Wolf

ORCID

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 118

Top Venues

Publications

Shuang Ni, Adrien Aumon, Guy Wolf, Kevin R. Moon, Jake S. Rhodes
Enhancing Supervised Visualization through Autoencoder and Random Forest Proximities for Out-of-Sample Extension. CoRR (2024)
Danqi Liao, Chen Liu, Benjamin W. Christensen, Alexander Tong, Guillaume Huguet, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy
Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy. CISS (2024)
Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michal Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. ICLR (2024)
Chenqing Hua, Connor W. Coley, Guy Wolf, Doina Precup, Shuangjia Zheng
Effective Protein-Protein Interaction Exploration with PPIretrieval. CoRR (2024)
Stefan Horoi, Albert Manuel Orozco Camacho, Eugene Belilovsky, Guy Wolf
Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis. CoRR (2024)
Frederik Wenkel, Semih Cantürk, Michael Perlmutter, Guy Wolf
Towards a General GNN Framework for Combinatorial Optimization. CoRR (2024)
Damien Martins Gomes, Yanlei Zhang, Eugene Belilovsky, Guy Wolf, Mahdi S. Hosseini
AdaFisher: Adaptive Second Order Optimization via Fisher Information. CoRR (2024)
Pedro Vianna, Muawiz Chaudhary, Paria Mehrbod, An Tang, Guy Cloutier, Guy Wolf, Michael Eickenberg, Eugene Belilovsky
Channel-Selective Normalization for Label-Shift Robust Test-Time Adaptation. CoRR (2024)
Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio
Simulation-Free Schrödinger Bridges via Score and Flow Matching. AISTATS (2024)
Sitao Luan, Chenqing Hua, Qincheng Lu, Liheng Ma, Lirong Wu, Xinyu Wang, Minkai Xu, Xiao-Wen Chang, Doina Precup, Rex Ying, Stan Z. Li, Jian Tang, Guy Wolf, Stefanie Jegelka
The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges. CoRR (2024)
Alexander Tong, Frederik Wenkel, Dhananjay Bhaskar, Kincaid MacDonald, Jackson D. Grady, Michael Perlmutter, Smita Krishnaswamy, Guy Wolf
Learnable Filters for Geometric Scattering Modules. IEEE Trans. Signal Process. 72 (2024)
Haozhe Chen, Andres Felipe Duque Correa, Guy Wolf, Kevin R. Moon
Noisy Data Visualization using Functional Data Analysis. CoRR (2024)
Alexander Tong, Kilian Fatras, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Guy Wolf, Yoshua Bengio
Improving and generalizing flow-based generative models with minibatch optimal transport. Trans. Mach. Learn. Res. 2024 (2024)
Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy
A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction. CoRR (2023)
Dhananjay Bhaskar, Yanlei Zhang, Charles Xu, Xingzhi Sun, Oluwadamilola Fasina, Guy Wolf, Maximilian Nickel, Michael Perlmutter, Smita Krishnaswamy
Graph topological property recovery with heat and wave dynamics-based features on graphs. CoRR (2023)
Dhananjay Bhaskar, Daniel Sumner Magruder, Edward De Brouwer, Aarthi Venkat, Frederik Wenkel, Guy Wolf, Smita Krishnaswamy
Inferring dynamic regulatory interaction graphs from time series data with perturbations. CoRR (2023)
Sacha Morin, Somjit Nath, Samira Ebrahimi Kahou, Guy Wolf
Spectral Temporal Contrastive Learning. CoRR (2023)
MohammadReza Davari, Stefan Horoi, Amine Natik, Guillaume Lajoie, Guy Wolf, Eugene Belilovsky
Reliability of CKA as a Similarity Measure in Deep Learning. ICLR (2023)
Dhananjay Bhaskar, Daniel Sumner Magruder, Matheo Morales, Edward De Brouwer, Aarthi Venkat, Frederik Wenkel, Guy Wolf, Smita Krishnaswamy
Inferring Dynamic Regulatory Interaction Graphs From Time Series Data With Perturbations. LoG (2023)
Michael Perlmutter, Alexander Tong, Feng Gao, Guy Wolf, Matthew J. Hirn
Understanding Graph Neural Networks with Generalized Geometric Scattering Transforms. SIAM J. Math. Data Sci. 5 (4) (2023)
Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio
Simulation-free Schrödinger bridges via score and flow matching. CoRR (2023)
Andrés F. Duque, Guy Wolf, Kevin R. Moon
Diffusion Transport Alignment. IDA (2023)
Oluwadamilola Fasina, Guillaume Huguet, Alexander Tong, Yanlei Zhang, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy
Neural FIM for learning Fisher Information Metrics from point cloud data. CoRR (2023)
Mostafa ElAraby, Guy Wolf, Margarida Carvalho
OAMIP: Optimizing ANN Architectures Using Mixed-Integer Programming. CPAIOR (2023)
Alexander Tong, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Kilian Fatras, Guy Wolf, Yoshua Bengio
Conditional Flow Matching: Simulation-Free Dynamic Optimal Transport. CoRR (2023)
Renming Liu, Semih Cantürk, Olivier Lapointe-Gagné, Vincent Létourneau, Guy Wolf, Dominique Beaini, Ladislav Rampásek
Graph Positional and Structural Encoder. CoRR (2023)
Samuel Leone, Aarthi Venkat, Guillaume Huguet, Alexander Tong, Guy Wolf, Smita Krishnaswamy
Graph Fourier MMD for Signals on Graphs. CoRR (2023)
Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michal Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Ioannis Koutis, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. CoRR (2023)
Danqi Liao, Chen Liu, Benjamin W. Christensen, Alexander Tong, Guillaume Huguet, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy
Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy. CoRR (2023)
Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy
A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction. NeurIPS (2023)
Andrés F. Duque, Sacha Morin, Guy Wolf, Kevin R. Moon
Geometry Regularized Autoencoders. IEEE Trans. Pattern Anal. Mach. Intell. 45 (6) (2023)
Oluwadamilola Fasina, Guillaume Huguet, Alexander Tong, Yanlei Zhang, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy
Neural FIM for learning Fisher information metrics from point cloud data. ICML (2023)
Guillaume Huguet, Alexander Tong, María Ramos Zapatero, Christopher J. Tape, Guy Wolf, Smita Krishnaswamy
Geodesic Sinkhorn For Fast and Accurate Optimal Transport on Manifolds. MLSP (2023)
Erica L. Busch, Jessie Huang, Andrew Benz, Tom Wallenstein, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy, Nicholas B. Turk-Browne
Multi-view manifold learning of human brain-state trajectories. Nat. Comput. Sci. 3 (3) (2023)
Guillaume Huguet, Alexander Tong, Bastian Rieck, Jessie Huang, Manik Kuchroo, Matthew J. Hirn, Guy Wolf, Smita Krishnaswamy
Time-Inhomogeneous Diffusion Geometry and Topology. SIAM J. Math. Data Sci. 5 (2) (2023)
Vijay Prakash Dwivedi, Ladislav Rampásek, Mikhail Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini
Long Range Graph Benchmark. CoRR (2022)
MohammadReza Davari, Stefan Horoi, Amine Natik, Guillaume Lajoie, Guy Wolf, Eugene Belilovsky
Reliability of CKA as a Similarity Measure in Deep Learning. CoRR (2022)
Guillaume Huguet, Alexander Tong, Bastian Rieck, Jessie Huang, Manik Kuchroo, Matthew J. Hirn, Guy Wolf, Smita Krishnaswamy
Time-inhomogeneous diffusion geometry and topology. CoRR (2022)
Alexander Cloninger, Timothy Doster, Tegan Emerson, Manohar Kaul, Ira Ktena, Henry Kvinge, Nina Miolane, Bastian Rice, Sarah Tymochko, Guy Wolf
Preface. TAG-ML (2022)
Alexander Tong, Frederik Wenkel, Dhananjay Bhaskar, Kincaid MacDonald, Jackson D. Grady, Michael Perlmutter, Smita Krishnaswamy, Guy Wolf
Learnable Filters for Geometric Scattering Modules. CoRR (2022)
Alexander Tong, Guillaume Huguet, Dennis L. Shung, Amine Natik, Manik Kuchroo, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy
Embedding Signals on Graphs with Unbalanced Diffusion Earth Mover's Distance. ICASSP (2022)
Stefan Horoi, Jessie Huang, Bastian Rieck, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy
Exploring the Geometry and Topology of Neural Network Loss Landscapes. IDA (2022)
Jessie Huang, Erica L. Busch, Tom Wallenstein, Michal Gerasimiuk, Andrew Benz, Guillaume Lajoie, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy
Learning shared neural manifolds from multi-subject FMRI data. CoRR (2022)
Jessie Huang, Erica L. Busch, Tom Wallenstein, Michal Gerasimiuk, Andrew Benz, Guillaume Lajoie, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy
Learning Shared Neural Manifolds from Multi-Subject FMRI Data. MLSP (2022)
Frederik Wenkel, Yimeng Min, Matthew Hirn, Michael Perlmutter, Guy Wolf
Overcoming Oversmoothness in Graph Convolutional Networks via Hybrid Scattering Networks. CoRR (2022)
Vijay Prakash Dwivedi, Ladislav Rampásek, Michael Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini
Long Range Graph Benchmark. NeurIPS (2022)
Andrés F. Duque, Myriam Lizotte, Guy Wolf, Kevin R. Moon
Manifold Alignment with Label Information. CoRR (2022)
Guillaume Huguet, Daniel Sumner Magruder, Alexander Tong, Oluwadamilola Fasina, Manik Kuchroo, Guy Wolf, Smita Krishnaswamy
Manifold Interpolating Optimal-Transport Flows for Trajectory Inference. NeurIPS (2022)
Andrés F. Duque, Guy Wolf, Kevin R. Moon
Diffusion Transport Alignment. CoRR (2022)
Yimeng Min, Frederik Wenkel, Michael Perlmutter, Guy Wolf
Can Hybrid Geometric Scattering Networks Help Solve the Maximal Clique Problem? CoRR (2022)
Yimeng Min, Frederik Wenkel, Michael Perlmutter, Guy Wolf
Can Hybrid Geometric Scattering Networks Help Solve the Maximum Clique Problem? NeurIPS (2022)
Renming Liu, Semih Cantürk, Frederik Wenkel, Dylan Sandfelder, Devin Kreuzer, Anna Little, Sarah McGuire, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew J. Hirn, Guy Wolf, Ladislav Rampásek
Taxonomy of Benchmarks in Graph Representation Learning. CoRR (2022)
Ladislav Rampásek, Michael Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini
Recipe for a General, Powerful, Scalable Graph Transformer. NeurIPS (2022)
Guillaume Huguet, Alexander Tong, María Ramos Zapatero, Guy Wolf, Smita Krishnaswamy
Geodesic Sinkhorn: optimal transport for high-dimensional datasets. CoRR (2022)
Renming Liu, Semih Cantürk, Frederik Wenkel, Sarah McGuire, Xinyi Wang, Anna Little, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew J. Hirn, Guy Wolf, Ladislav Rampásek
Taxonomy of Benchmarks in Graph Representation Learning. LoG (2022)
Ladislav Rampásek, Mikhail Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini
Recipe for a General, Powerful, Scalable Graph Transformer. CoRR (2022)
Guillaume Huguet, Daniel Sumner Magruder, Oluwadamilola Fasina, Alexander Tong, Manik Kuchroo, Guy Wolf, Smita Krishnaswamy
Manifold Interpolating Optimal-Transport Flows for Trajectory Inference. CoRR (2022)
Alexander Tong, Guy Wolf, Smita Krishnaswamy
Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators. J. Signal Process. Syst. 94 (2) (2022)
Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Muawiz Chaudhary, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf
Parametric Scattering Networks. CVPR (2022)
Alexander Tong, Guillaume Huguet, Dennis L. Shung, Amine Natik, Manik Kuchroo, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy
Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance. CoRR (2021)
Manik Kuchroo, Abhinav Godavarthi, Guy Wolf, Smita Krishnaswamy
Multimodal data visualization, denoising and clustering with integrated diffusion. CoRR (2021)
Manik Kuchroo, Abhinav Godavarthi, Alexander Tong, Guy Wolf, Smita Krishnaswamy
Multimodal Data Visualization and Denoising with Integrated Diffusion. MLSP (2021)
Michal Gerasimiuk, Dennis L. Shung, Alexander Tong, Adrian J. Stanley, Michael Schultz, Jeffrey Ngu, Loren Laine, Guy Wolf, Smita Krishnaswamy
MURAL: An Unsupervised Random Forest-Based Embedding for Electronic Health Record Data. CoRR (2021)
Renming Liu, Semih Cantürk, Frederik Wenkel, Dylan Sandfelder, Devin Kreuzer, Anna Little, Sarah McGuire, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew Hirn, Guy Wolf, Ladislav Rampásek
Towards a Taxonomy of Graph Learning Datasets. CoRR (2021)
Guy Wolf, Gil Shabat, Hanan Shteingart
Positivity Validation Detection and Explainability via Zero Fraction Multi-Hypothesis Testing and Asymmetrically Pruned Decision Trees. CoRR (2021)
Alexander Tong, Guillaume Huguet, Amine Natik, Kincaid MacDonald, Manik Kuchroo, Ronald R. Coifman, Guy Wolf, Smita Krishnaswamy
Diffusion Earth Mover's Distance and Distribution Embeddings. ICML (2021)
Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf
Parametric Scattering Networks. CoRR (2021)
Alexander Tong, Frederick Wenkel, Kincaid MacDonald, Smita Krishnaswamy, Guy Wolf
Data-Driven Learning of Geometric Scattering Modules for GNNs. MLSP (2021)
Ladislav Rampásek, Guy Wolf
Hierarchical graph neural nets can capture long-range interactions. CoRR (2021)
Michal Gerasimiuk, Dennis L. Shung, Alexander Tong, Adrian J. Stanley, Michael Schultz, Jeffrey Ngu, Loren Laine, Guy Wolf, Smita Krishnaswamy
MURAL: An Unsupervised Random Forest-Based Embedding for Electronic Health Record Data. IEEE BigData (2021)
Jake S. Rhodes, Adele Cutler, Guy Wolf, Kevin R. Moon
Random Forest-Based Diffusion Information Geometry for Supervised Visualization and Data Exploration. SSP (2021)
Yimeng Min, Frederik Wenkel, Guy Wolf
Geometric Scattering Attention Networks. ICASSP (2021)
Alexander Tong, Guillaume Huguet, Amine Natik, Kincaid MacDonald, Manik Kuchroo, Ronald R. Coifman, Guy Wolf, Smita Krishnaswamy
Diffusion Earth Mover's Distance and Distribution Embeddings. CoRR (2021)
Stefan Horoi, Jessie Huang, Guy Wolf, Smita Krishnaswamy
Visualizing High-Dimensional Trajectories on the Loss-Landscape of ANNs. CoRR (2021)
Ladislav Rampásek, Guy Wolf
Hierarchical Graph Neural Nets can Capture Long-Range Interactions. MLSP (2021)
Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. CoRR (2020)
Bastian Rieck, Tristan Yates, Christian Bock, Karsten M. Borgwardt, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy
Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence. NeurIPS (2020)
Yimeng Min, Frederik Wenkel, Guy Wolf
Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks. CoRR (2020)
Michael Perlmutter, Feng Gao, Guy Wolf, Matthew J. Hirn
Geometric Wavelet Scattering Networks on Compact Riemannian Manifolds. MSML (2020)
Egbert Castro, Andrew Benz, Alexander Tong, Guy Wolf, Smita Krishnaswamy
Uncovering the Folding Landscape of RNA Secondary Structure Using Deep Graph Embeddings. IEEE BigData (2020)
Bastian Rieck, Tristan Yates, Christian Bock, Karsten M. Borgwardt, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy
Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence. CoRR (2020)
Andrés F. Duque, Sacha Morin, Guy Wolf, Kevin R. Moon
Extendable and invertible manifold learning with geometry regularized autoencoders. IEEE BigData (2020)
Egbert Castro, Andrew Benz, Alexander Tong, Guy Wolf, Smita Krishnaswamy
Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings. CoRR (2020)
Yimeng Min, Frederik Wenkel, Guy Wolf
Geometric Scattering Attention Networks. CoRR (2020)
Yimeng Min, Frederik Wenkel, Guy Wolf
Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks. NeurIPS (2020)
Jake S. Rhodes, Adele Cutler, Guy Wolf, Kevin R. Moon
Supervised Visualization for Data Exploration. CoRR (2020)
Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. ICML (2020)
Jay S. Stanley III, Scott Gigante, Guy Wolf, Smita Krishnaswamy
Harmonic Alignment. SDM (2020)
Alexander Tong, Guy Wolf, Smita Krishnaswamy
Fixing Bias in Reconstruction-Based Anomaly Detection with Lipschitz Discriminators. MLSP (2020)
Matthew Amodio, David van Dijk, Guy Wolf, Smita Krishnaswamy
Learning General Transformations of Data for Out-of-Sample Extensions. MLSP (2020)
Stefan Horoi, Guillaume Lajoie, Guy Wolf
Internal representation dynamics and geometry in recurrent neural networks. CoRR (2020)
Stefan Horoi, Victor Geadah, Guy Wolf, Guillaume Lajoie
Low-Dimensional Dynamics of Encoding and Learning in Recurrent Neural Networks. Canadian Conference on AI (2020)
Mostafa ElAraby, Guy Wolf, Margarida Carvalho
Identifying Critical Neurons in ANN Architectures using Mixed Integer Programming. CoRR (2020)
Andrés F. Duque, Sacha Morin, Guy Wolf, Kevin R. Moon
Extendable and invertible manifold learning with geometry regularized autoencoders. CoRR (2020)
Alexander Tong, David van Dijk, Jay S. Stanley III, Matthew Amodio, Kristina Yim, Rebecca Muhle, James Noonan, Guy Wolf, Smita Krishnaswamy
Interpretable Neuron Structuring with Graph Spectral Regularization. IDA (2020)
Victor Geadah, Giancarlo Kerg, Stefan Horoi, Guy Wolf, Guillaume Lajoie
Advantages of biologically-inspired adaptive neural activation in RNNs during learning. CoRR (2020)
Alexander Tong, Frederik Wenkel, Kincaid MacDonald, Smita Krishnaswamy, Guy Wolf
Data-Driven Learning of Geometric Scattering Networks. CoRR (2020)
David van Dijk, Daniel B. Burkhardt, Matthew Amodio, Alexander Tong, Guy Wolf, Smita Krishnaswamy
Finding Archetypal Spaces Using Neural Networks. IEEE BigData (2019)
Nathan Brugnone, Smita Krishnaswamy, Alex Gonopolskiy, Mark W. Moyle, Manik Kuchroo, David van Dijk, Kevin R. Moon, Daniel Colón-Ramos, Guy Wolf, Matthew J. Hirn
Coarse Graining of Data via Inhomogeneous Diffusion Condensation. IEEE BigData (2019)
Michael Perlmutter, Feng Gao, Guy Wolf, Matthew J. Hirn
Understanding Graph Neural Networks with Asymmetric Geometric Scattering Transforms. CoRR (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Guy Wolf