Guy Wolf

Orcid: 0000-0002-6740-059X

According to our database¹, Guy Wolf authored at least 102 papers between 2012 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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In proceedings

Article

PhD thesis

Dataset

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Links

On csauthors.net:

Bibliography

2024

Learnable Filters for Geometric Scattering Modules.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2024

Improving and generalizing flow-based generative models with minibatch optimal transport.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2024

EnzymeFlow: Generating Reaction-specific Enzyme Catalytic Pockets through Flow Matching and Co-Evolutionary Dynamics.

[BibT_eX]

[DOI]

CoRR, 2024

Are Heterophily-Specific GNNs and Homophily Metrics Really Effective? Evaluation Pitfalls and New Benchmarks.

[BibT_eX]

[DOI]

CoRR, 2024

Reactzyme: A Benchmark for Enzyme-Reaction Prediction.

[BibT_eX]

[DOI]

CoRR, 2024

The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges.

[BibT_eX]

[DOI]

CoRR, 2024

Enhancing Supervised Visualization through Autoencoder and Random Forest Proximities for Out-of-Sample Extension.

[BibT_eX]

[DOI]

CoRR, 2024

Noisy Data Visualization using Functional Data Analysis.

[BibT_eX]

[DOI]

Haozhe Chen

Andres Felipe Duque Correa

Guy Wolf

Kevin R. Moon

CoRR, 2024

Towards a General GNN Framework for Combinatorial Optimization.

[BibT_eX]

[DOI]

CoRR, 2024

AdaFisher: Adaptive Second Order Optimization via Fisher Information.

[BibT_eX]

[DOI]

CoRR, 2024

Channel-Selective Normalization for Label-Shift Robust Test-Time Adaptation.

[BibT_eX]

[DOI]

CoRR, 2024

Effective Protein-Protein Interaction Exploration with PPIretrieval.

[BibT_eX]

[DOI]

CoRR, 2024

Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis.

[BibT_eX]

[DOI]

Stefan Horoi

Albert Manuel Orozco Camacho

Eugene Belilovsky

Guy Wolf

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Graph Positional and Structural Encoder.

[BibT_eX]

[DOI]

Semih Cantürk

Renming Liu

Olivier Lapointe-Gagné

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy.

[BibT_eX]

[DOI]

Danqi Liao

Chen Liu

Benjamin W. Christensen

Proceedings of the 58th Annual Conference on Information Sciences and Systems, 2024

Simulation-Free Schrödinger Bridges via Score and Flow Matching.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Understanding Graph Neural Networks with Generalized Geometric Scattering Transforms.

[BibT_eX]

[DOI]

SIAM J. Math. Data Sci., December, 2023

Time-Inhomogeneous Diffusion Geometry and Topology.

[BibT_eX]

[DOI]

SIAM J. Math. Data Sci., June, 2023

Geometry Regularized Autoencoders.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., June, 2023

Multi-view manifold learning of human brain-state trajectories.

[BibT_eX]

[DOI]

Nicholas B. Turk-Browne

Nat. Comput. Sci., 2023

Spectral Temporal Contrastive Learning.

[BibT_eX]

[DOI]

Sacha Morin

Somjit Nath

Samira Ebrahimi Kahou

Guy Wolf

CoRR, 2023

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets.

[BibT_eX]

[DOI]

CoRR, 2023

Graph topological property recovery with heat and wave dynamics-based features on graphs.

[BibT_eX]

[DOI]

CoRR, 2023

Inferring dynamic regulatory interaction graphs from time series data with perturbations.

[BibT_eX]

[DOI]

Dhananjay Bhaskar

Daniel Sumner Magruder

CoRR, 2023

Graph Fourier MMD for Signals on Graphs.

[BibT_eX]

[DOI]

CoRR, 2023

Conditional Flow Matching: Simulation-Free Dynamic Optimal Transport.

[BibT_eX]

[DOI]

CoRR, 2023

A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Geodesic Sinkhorn For Fast and Accurate Optimal Transport on Manifolds.

[BibT_eX]

[DOI]

Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

Inferring Dynamic Regulatory Interaction Graphs From Time Series Data With Perturbations.

[BibT_eX]

[DOI]

Dhananjay Bhaskar

Daniel Sumner Magruder

Proceedings of the Learning on Graphs Conference, 27-30 November 2023, Virtual Event., 2023

Diffusion Transport Alignment.

[BibT_eX]

[DOI]

Andrés F. Duque

Guy Wolf

Kevin R. Moon

Proceedings of the Advances in Intelligent Data Analysis XXI, 2023

Neural FIM for learning Fisher information metrics from point cloud data.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Reliability of CKA as a Similarity Measure in Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

OAMIP: Optimizing ANN Architectures Using Mixed-Integer Programming.

[BibT_eX]

[DOI]

Mostafa ElAraby

Guy Wolf

Margarida Carvalho

Proceedings of the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2023

2022

Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators.

[BibT_eX]

[DOI]

Alexander Tong

Guy Wolf

Smita Krishnaswamy

J. Signal Process. Syst., 2022

Geodesic Sinkhorn: optimal transport for high-dimensional datasets.

[BibT_eX]

[DOI]

CoRR, 2022

Manifold Alignment with Label Information.

[BibT_eX]

[DOI]

CoRR, 2022

Taxonomy of Benchmarks in Graph Representation Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Can Hybrid Geometric Scattering Networks Help Solve the Maximal Clique Problem?

[BibT_eX]

[DOI]

CoRR, 2022

Overcoming Oversmoothness in Graph Convolutional Networks via Hybrid Scattering Networks.

[BibT_eX]

[DOI]

CoRR, 2022

Preface.

[BibT_eX]

[DOI]

Proceedings of the Topological, 2022

Recipe for a General, Powerful, Scalable Graph Transformer.

[BibT_eX]

[DOI]

Ladislav Rampásek

Michael Galkin

Vijay Prakash Dwivedi

Anh Tuan Luu

Guy Wolf

Dominique Beaini

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Can Hybrid Geometric Scattering Networks Help Solve the Maximum Clique Problem?

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Manifold Interpolating Optimal-Transport Flows for Trajectory Inference.

[BibT_eX]

[DOI]

Guillaume Huguet

Daniel Sumner Magruder

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Long Range Graph Benchmark.

[BibT_eX]

[DOI]

Vijay Prakash Dwivedi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Shared Neural Manifolds from Multi-Subject FMRI Data.

[BibT_eX]

[DOI]

Nicholas B. Turk-Browne

Smita Krishnaswamy

Proceedings of the 32nd IEEE International Workshop on Machine Learning for Signal Processing, 2022

Taxonomy of Benchmarks in Graph Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the Learning on Graphs Conference, 2022

Exploring the Geometry and Topology of Neural Network Loss Landscapes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Intelligent Data Analysis XX, 2022

Embedding Signals on Graphs with Unbalanced Diffusion Earth Mover's Distance.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2022

Parametric Scattering Networks.

[BibT_eX]

[DOI]

Shanel Gauthier

Benjamin Thérien

Laurent Alsène-Racicot

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Positivity Validation Detection and Explainability via Zero Fraction Multi-Hypothesis Testing and Asymmetrically Pruned Decision Trees.

[BibT_eX]

[DOI]

Guy Wolf

Gil Shabat

Hanan Shteingart

CoRR, 2021

Towards a Taxonomy of Graph Learning Datasets.

[BibT_eX]

[DOI]

CoRR, 2021

Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance.

[BibT_eX]

[DOI]

CoRR, 2021

Parametric Scattering Networks.

[BibT_eX]

[DOI]

Shanel Gauthier

Benjamin Thérien

Laurent Alsène-Racicot

CoRR, 2021

Multimodal data visualization, denoising and clustering with integrated diffusion.

[BibT_eX]

[DOI]

CoRR, 2021

Visualizing High-Dimensional Trajectories on the Loss-Landscape of ANNs.

[BibT_eX]

[DOI]

CoRR, 2021

Random Forest-Based Diffusion Information Geometry for Supervised Visualization and Data Exploration.

[BibT_eX]

[DOI]

Proceedings of the IEEE Statistical Signal Processing Workshop, 2021

Data-Driven Learning of Geometric Scattering Modules for GNNs.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), 2021

Hierarchical Graph Neural Nets can Capture Long-Range Interactions.

[BibT_eX]

[DOI]

Ladislav Rampásek

Guy Wolf

Proceedings of the 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), 2021

Multimodal Data Visualization and Denoising with Integrated Diffusion.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), 2021

Diffusion Earth Mover's Distance and Distribution Embeddings.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Geometric Scattering Attention Networks.

[BibT_eX]

[DOI]

Yimeng Min

Frederik Wenkel

Guy Wolf

Proceedings of the IEEE International Conference on Acoustics, 2021

MURAL: An Unsupervised Random Forest-Based Embedding for Electronic Health Record Data.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Data-Driven Learning of Geometric Scattering Networks.

[BibT_eX]

[DOI]

CoRR, 2020

Advantages of biologically-inspired adaptive neural activation in RNNs during learning.

[BibT_eX]

[DOI]

CoRR, 2020

Supervised Visualization for Data Exploration.

[BibT_eX]

[DOI]

CoRR, 2020

Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings.

[BibT_eX]

[DOI]

CoRR, 2020

Identifying Critical Neurons in ANN Architectures using Mixed Integer Programming.

[BibT_eX]

[DOI]

Mostafa ElAraby

Guy Wolf

Margarida Carvalho

CoRR, 2020

Internal representation dynamics and geometry in recurrent neural networks.

[BibT_eX]

[DOI]

Stefan Horoi

Guillaume Lajoie

Guy Wolf

CoRR, 2020

Harmonic Alignment.

[BibT_eX]

[DOI]

Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence.

[BibT_eX]

[DOI]

Nicholas B. Turk-Browne

Smita Krishnaswamy

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks.

[BibT_eX]

[DOI]

Yimeng Min

Frederik Wenkel

Guy Wolf

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Geometric Wavelet Scattering Networks on Compact Riemannian Manifolds.

[BibT_eX]

[DOI]

Proceedings of Mathematical and Scientific Machine Learning, 2020

Learning General Transformations of Data for Out-of-Sample Extensions.

[BibT_eX]

[DOI]

Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

Interpretable Neuron Structuring with Graph Spectral Regularization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Intelligent Data Analysis XVIII, 2020

TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Extendable and invertible manifold learning with geometry regularized autoencoders.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Uncovering the Folding Landscape of RNA Secondary Structure Using Deep Graph Embeddings.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Low-Dimensional Dynamics of Encoding and Learning in Recurrent Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Artificial Intelligence, 2020

2019

Understanding Graph Neural Networks with Asymmetric Geometric Scattering Transforms.

[BibT_eX]

[DOI]

CoRR, 2019

A Lipschitz-constrained anomaly discriminator framework.

[BibT_eX]

[DOI]

Alexander Tong

Guy Wolf

Smita Krishnaswamy

CoRR, 2019

Compressed Diffusion.

[BibT_eX]

[DOI]

CoRR, 2019

Finding Archetypal Spaces for Data Using Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2019

Visualizing High Dimensional Dynamical Processes.

[BibT_eX]

[DOI]

Andrés F. Duque

Guy Wolf

Kevin R. Moon

Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019

Geometric Scattering for Graph Data Analysis.

[BibT_eX]

[DOI]

Feng Gao

Guy Wolf

Matthew J. Hirn

Proceedings of the 36th International Conference on Machine Learning, 2019

Vertex-Frequency Clustering.

[BibT_eX]

[DOI]

Proceedings of the IEEE Data Science Workshop, 2019

Finding Archetypal Spaces Using Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Coarse Graining of Data via Inhomogeneous Diffusion Condensation.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Geometric Scattering on Manifolds.

[BibT_eX]

[DOI]

Michael Perlmutter

Guy Wolf

Matthew J. Hirn

CoRR, 2018

Graph Classification with Geometric Scattering.

[BibT_eX]

[DOI]

Feng Gao

Guy Wolf

Matthew J. Hirn

CoRR, 2018

Graph Spectral Regularization for Neural Network Interpretability.

[BibT_eX]

[DOI]

CoRR, 2018

Manifold Alignment with Feature Correspondence.

[BibT_eX]

[DOI]

Jay S. Stanley III

Guy Wolf

Smita Krishnaswamy

CoRR, 2018

Modeling Dynamics with Deep Transition-Learning Networks.

[BibT_eX]

[DOI]

David van Dijk

Scott Gigante

Alexander Strzalkowski

Guy Wolf

Smita Krishnaswamy

CoRR, 2018

Geometry Based Data Generation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2016

Rigid Motion Model for Audio Source Separation.

[BibT_eX]

[DOI]

Guy Wolf

Stéphane Mallat

Shihab A. Shamma

IEEE Trans. Signal Process., 2016

Learning from patches by efficient spectral decomposition of a structured kernel.

[BibT_eX]

[DOI]

Mach. Learn., 2016

2015

Diffusion Representations.

[BibT_eX]

[DOI]

CoRR, 2015

2014

Audio source separation with time-frequency velocities.

[BibT_eX]

[DOI]

Guy Wolf

Stéphane Mallat

Shihab A. Shamma

Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

Parameter Rating by Diffusion Gradient.

[BibT_eX]

[DOI]

Guy Wolf

Amir Averbuch

Pekka Neittaanmäki

Proceedings of the Modeling, Simulation and Optimization for Science and Technology, 2014

2013

Diffusion-based analysis of locally low-dimensional geometries in high-dimensional data

[BibT_eX]

[DOI]

Guy Wolf

PhD thesis, 2013

2012

Dictionary Construction for Patch-to-Tensor Embedding.

[BibT_eX]

[DOI]

Proceedings of the Advances in Intelligent Data Analysis XI - 11th International Symposium, 2012

Patch-Based Data Analysis Using Linear-Projection Diffusion.

[BibT_eX]

[DOI]

Proceedings of the Advances in Intelligent Data Analysis XI - 11th International Symposium, 2012

Guy Wolf

Timeline

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On csauthors.net:

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