Patch-Based Data Analysis Using Linear-Projection Diffusion. - Moshe Salhov; Guy Wolf; Amir Averbuch; Pekka Neittaanmäki (IDA, 2012)

Dictionary Construction for Patch-to-Tensor Embedding. - Moshe Salhov; Guy Wolf; Amit Bermanis; Amir Averbuch; Pekka Neittaanmäki (IDA, 2012)

Diffusion-based analysis of locally low-dimensional geometries in high-dimensional data - Guy Wolf (2013)

Parameter Rating by Diffusion Gradient. - Guy Wolf; Amir Averbuch; Pekka Neittaanmäki (Modeling, Simulation and Optimization for Science and Technology, 2014)

Audio source separation with time-frequency velocities. - Guy Wolf; Stéphane Mallat; Shihab A. Shamma (MLSP, 2014)

Diffusion Representations. - Moshe Salhov; Amit Bermanis; Guy Wolf; Amir Averbuch (CoRR, 2015)

Learning from patches by efficient spectral decomposition of a structured kernel. - Moshe Salhov; Amit Bermanis; Guy Wolf; Amir Averbuch (Mach. Learn., 2016)

Rigid Motion Model for Audio Source Separation. - Guy Wolf; Stéphane Mallat; Shihab A. Shamma (IEEE Trans. Signal Process., 2016)

Geometry Based Data Generation. - Ofir Lindenbaum; Jay S. Stanley III; Guy Wolf; Smita Krishnaswamy (NeurIPS, 2018)

Modeling Dynamics with Deep Transition-Learning Networks. - David van Dijk; Scott Gigante; Alexander Strzalkowski; Guy Wolf; Smita Krishnaswamy (CoRR, 2018)

Manifold Alignment with Feature Correspondence. - Jay S. Stanley III; Guy Wolf; Smita Krishnaswamy (CoRR, 2018)

Graph Spectral Regularization for Neural Network Interpretability. - Alexander Tong 001; David van Dijk; Jay S. Stanley III; Matthew Amodio; Guy Wolf; Smita Krishnaswamy (CoRR, 2018)

Graph Classification with Geometric Scattering. - Feng Gao; Guy Wolf; Matthew J. Hirn (CoRR, 2018)

Geometric Scattering on Manifolds. - Michael Perlmutter; Guy Wolf; Matthew J. Hirn (CoRR, 2018)

Coarse Graining of Data via Inhomogeneous Diffusion Condensation. - 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 (IEEE BigData, 2019)

Finding Archetypal Spaces Using Neural Networks. - David van Dijk; Daniel B. Burkhardt; Matthew Amodio; Alexander Tong 001; Guy Wolf; Smita Krishnaswamy (IEEE BigData, 2019)

Vertex-Frequency Clustering. - Daniel B. Burkhardt; Jay S. Stanley III; Guy Wolf; Smita Krishnaswamy (DSW, 2019)

Geometric Scattering for Graph Data Analysis. - Feng Gao; Guy Wolf; Matthew J. Hirn (ICML, 2019)

Visualizing High Dimensional Dynamical Processes. - Andrés F. Duque; Guy Wolf; Kevin R. Moon (MLSP, 2019)

Finding Archetypal Spaces for Data Using Neural Networks. - David van Dijk; Daniel B. Burkhardt; Matthew Amodio; Alexander Tong 001; Guy Wolf; Smita Krishnaswamy (CoRR, 2019)

Compressed Diffusion. - Scott Gigante; Jay S. Stanley III; Ngan Vu; David van Dijk; Kevin R. Moon; Guy Wolf; Smita Krishnaswamy (CoRR, 2019)

A Lipschitz-constrained anomaly discriminator framework. - Alexander Tong 001; Guy Wolf; Smita Krishnaswamy (CoRR, 2019)

Understanding Graph Neural Networks with Asymmetric Geometric Scattering Transforms. - Michael Perlmutter; Feng Gao; Guy Wolf; Matthew J. Hirn (CoRR, 2019)

Low-Dimensional Dynamics of Encoding and Learning in Recurrent Neural Networks. - Stefan Horoi; Victor Geadah; Guy Wolf; Guillaume Lajoie (Canadian AI, 2020)

Uncovering the Folding Landscape of RNA Secondary Structure Using Deep Graph Embeddings. - Egbert Castro; Andrew Benz; Alexander Tong 001; Guy Wolf; Smita Krishnaswamy (IEEE BigData, 2020)

Extendable and invertible manifold learning with geometry regularized autoencoders. - Andrés F. Duque; Sacha Morin; Guy Wolf; Kevin R. Moon (IEEE BigData, 2020)

TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. - Alexander Tong 001; Jessie Huang; Guy Wolf; David van Dijk; Smita Krishnaswamy (ICML, 2020)

Interpretable Neuron Structuring with Graph Spectral Regularization. - Alexander Tong 001; David van Dijk; Jay S. Stanley III; Matthew Amodio; Kristina Yim; Rebecca Muhle; James Noonan; Guy Wolf; Smita Krishnaswamy (IDA, 2020)

Learning General Transformations of Data for Out-of-Sample Extensions. - Matthew Amodio; David van Dijk; Guy Wolf; Smita Krishnaswamy (MLSP, 2020)

Geometric Wavelet Scattering Networks on Compact Riemannian Manifolds. - Michael Perlmutter; Feng Gao; Guy Wolf; Matthew J. Hirn (MSML, 2020)

Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks. - Yimeng Min; Frederik Wenkel; Guy Wolf (NeurIPS, 2020)

Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence. - Bastian Rieck; Tristan Yates; Christian Bock; Karsten M. Borgwardt; Guy Wolf; Nicholas B. Turk-Browne; Smita Krishnaswamy (NeurIPS, 2020)

Harmonic Alignment. - Jay S. Stanley III; Scott Gigante; Guy Wolf; Smita Krishnaswamy (SDM, 2020)

Internal representation dynamics and geometry in recurrent neural networks. - Stefan Horoi; Guillaume Lajoie; Guy Wolf (CoRR, 2020)

Identifying Critical Neurons in ANN Architectures using Mixed Integer Programming. - Mostafa ElAraby; Guy Wolf; Margarida Carvalho (CoRR, 2020)

Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings. - Egbert Castro; Andrew Benz; Alexander Tong 001; Guy Wolf; Smita Krishnaswamy (CoRR, 2020)

Supervised Visualization for Data Exploration. - Jake S. Rhodes; Adele Cutler; Guy Wolf; Kevin R. Moon (CoRR, 2020)

Advantages of biologically-inspired adaptive neural activation in RNNs during learning. - Victor Geadah; Giancarlo Kerg; Stefan Horoi; Guy Wolf; Guillaume Lajoie (CoRR, 2020)

Data-Driven Learning of Geometric Scattering Networks. - Alexander Tong 001; Frederik Wenkel; Kincaid MacDonald; Smita Krishnaswamy; Guy Wolf (CoRR, 2020)

MURAL: An Unsupervised Random Forest-Based Embedding for Electronic Health Record Data. - Michal Gerasimiuk; Dennis L. Shung; Alexander Tong 001; Adrian J. Stanley; Michael Schultz; Jeffrey Ngu; Loren Laine; Guy Wolf; Smita Krishnaswamy (IEEE BigData, 2021)

Geometric Scattering Attention Networks. - Yimeng Min; Frederik Wenkel; Guy Wolf (ICASSP, 2021)

Diffusion Earth Mover's Distance and Distribution Embeddings. - Alexander Tong 001; Guillaume Huguet; Amine Natik; Kincaid MacDonald; Manik Kuchroo; Ronald R. Coifman; Guy Wolf; Smita Krishnaswamy (ICML, 2021)

Multimodal Data Visualization and Denoising with Integrated Diffusion. - Manik Kuchroo; Abhinav Godavarthi; Alexander Tong 001; Guy Wolf; Smita Krishnaswamy (MLSP, 2021)

Hierarchical Graph Neural Nets can Capture Long-Range Interactions. - Ladislav Rampásek; Guy Wolf (MLSP, 2021)

Data-Driven Learning of Geometric Scattering Modules for GNNs. - Alexander Tong 001; Frederick Wenkel; Kincaid MacDonald; Smita Krishnaswamy; Guy Wolf (MLSP, 2021)

Random Forest-Based Diffusion Information Geometry for Supervised Visualization and Data Exploration. - Jake S. Rhodes; Adele Cutler; Guy Wolf; Kevin R. Moon (SSP, 2021)

Visualizing High-Dimensional Trajectories on the Loss-Landscape of ANNs. - Stefan Horoi; Jessie Huang; Guy Wolf; Smita Krishnaswamy (CoRR, 2021)

Multimodal data visualization, denoising and clustering with integrated diffusion. - Manik Kuchroo; Abhinav Godavarthi; Guy Wolf; Smita Krishnaswamy (CoRR, 2021)

Parametric Scattering Networks. - Shanel Gauthier; Benjamin Thérien; Laurent Alsène-Racicot; Irina Rish; Eugene Belilovsky; Michael Eickenberg; Guy Wolf (CoRR, 2021)

Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance. - Alexander Tong 001; Guillaume Huguet; Dennis L. Shung; Amine Natik; Manik Kuchroo; Guillaume Lajoie; Guy Wolf; Smita Krishnaswamy (CoRR, 2021)

Towards a Taxonomy of Graph Learning Datasets. - 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; et al. (CoRR, 2021)

Positivity Validation Detection and Explainability via Zero Fraction Multi-Hypothesis Testing and Asymmetrically Pruned Decision Trees. - Guy Wolf; Gil Shabat; Hanan Shteingart (CoRR, 2021)

Parametric Scattering Networks. - Shanel Gauthier; Benjamin Thérien; Laurent Alsène-Racicot; Muawiz Chaudhary; Irina Rish; Eugene Belilovsky; Michael Eickenberg; Guy Wolf (CVPR, 2022)

Embedding Signals on Graphs with Unbalanced Diffusion Earth Mover's Distance. - Alexander Tong 001; Guillaume Huguet; Dennis L. Shung; Amine Natik; Manik Kuchroo; Guillaume Lajoie; Guy Wolf; Smita Krishnaswamy (ICASSP, 2022)

Exploring the Geometry and Topology of Neural Network Loss Landscapes. - Stefan Horoi; Jessie Huang; Bastian Rieck; Guillaume Lajoie; Guy Wolf; Smita Krishnaswamy (IDA, 2022)

Taxonomy of Benchmarks in Graph Representation Learning. - 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 (LoG, 2022)

Learning Shared Neural Manifolds from Multi-Subject FMRI Data. - Jessie Huang; Erica L. Busch; Tom Wallenstein; Michal Gerasimiuk; Andrew Benz; Guillaume Lajoie; Guy Wolf; Nicholas B. Turk-Browne; Smita Krishnaswamy (MLSP, 2022)

Long Range Graph Benchmark. - Vijay Prakash Dwivedi; Ladislav Rampásek; Michael Galkin; Ali Parviz; Guy Wolf; Anh Tuan Luu; Dominique Beaini (NeurIPS, 2022)

Manifold Interpolating Optimal-Transport Flows for Trajectory Inference. - Guillaume Huguet; Daniel Sumner Magruder; Alexander Tong 001; Oluwadamilola Fasina; Manik Kuchroo; Guy Wolf; Smita Krishnaswamy (NeurIPS, 2022)

Can Hybrid Geometric Scattering Networks Help Solve the Maximum Clique Problem? - Yimeng Min; Frederik Wenkel; Michael Perlmutter; Guy Wolf (NeurIPS, 2022)

Recipe for a General, Powerful, Scalable Graph Transformer. - Ladislav Rampásek; Michael Galkin; Vijay Prakash Dwivedi; Anh Tuan Luu; Guy Wolf; Dominique Beaini (NeurIPS, 2022)

Preface. - Alexander Cloninger; Timothy Doster; Tegan Emerson; Manohar Kaul; Ira Ktena; Henry Kvinge; Nina Miolane; Bastian Rice; Sarah Tymochko; Guy Wolf (TAG-ML, 2022)

Overcoming Oversmoothness in Graph Convolutional Networks via Hybrid Scattering Networks. - Frederik Wenkel; Yimeng Min; Matthew J. Hirn; Michael Perlmutter; Guy Wolf (CoRR, 2022)

Can Hybrid Geometric Scattering Networks Help Solve the Maximal Clique Problem? - Yimeng Min; Frederik Wenkel; Michael Perlmutter; Guy Wolf (CoRR, 2022)

Taxonomy of Benchmarks in Graph Representation Learning. - 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; et al. (CoRR, 2022)

Manifold Alignment with Label Information. - Andrés F. Duque; Myriam Lizotte; Guy Wolf; Kevin R. Moon (CoRR, 2022)

Geodesic Sinkhorn: optimal transport for high-dimensional datasets. - Guillaume Huguet; Alexander Tong 001; María Ramos Zapatero; Guy Wolf; Smita Krishnaswamy (CoRR, 2022)

Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators. - Alexander Tong 001; Guy Wolf; Smita Krishnaswamy (J. Signal Process. Syst., 2022)

OAMIP: Optimizing ANN Architectures Using Mixed-Integer Programming. - Mostafa ElAraby; Guy Wolf; Margarida Carvalho (CPAIOR, 2023)

Reliability of CKA as a Similarity Measure in Deep Learning. - MohammadReza Davari; Stefan Horoi; Amine Natik; Guillaume Lajoie; Guy Wolf; Eugene Belilovsky (ICLR, 2023)

Neural FIM for learning Fisher information metrics from point cloud data. - Oluwadamilola Fasina; Guillaume Huguet; Alexander Tong 001; Yanlei Zhang; Guy Wolf; Maximilian Nickel; Ian Adelstein; Smita Krishnaswamy (ICML, 2023)

Diffusion Transport Alignment. - Andrés F. Duque; Guy Wolf; Kevin R. Moon (IDA, 2023)

Inferring Dynamic Regulatory Interaction Graphs From Time Series Data With Perturbations. - Dhananjay Bhaskar; Daniel Sumner Magruder; Matheo Morales; Edward De Brouwer; Aarthi Venkat; Frederik Wenkel; Guy Wolf; Smita Krishnaswamy (LoG, 2023)

Geodesic Sinkhorn For Fast and Accurate Optimal Transport on Manifolds. - Guillaume Huguet; Alexander Tong 001; María Ramos Zapatero; Christopher J. Tape; Guy Wolf; Smita Krishnaswamy (MLSP, 2023)

A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction. - Guillaume Huguet; Alexander Tong 001; Edward De Brouwer; Yanlei Zhang; Guy Wolf; Ian Adelstein; Smita Krishnaswamy (NeurIPS, 2023)

Conditional Flow Matching: Simulation-Free Dynamic Optimal Transport. - Alexander Tong 001; Nikolay Malkin; Guillaume Huguet; Yanlei Zhang; Jarrid Rector-Brooks; Kilian Fatras; Guy Wolf; Yoshua Bengio (CoRR, 2023)

Graph Fourier MMD for Signals on Graphs. - Samuel Leone; Aarthi Venkat; Guillaume Huguet; Alexander Tong 001; Guy Wolf; Smita Krishnaswamy (CoRR, 2023)

Inferring dynamic regulatory interaction graphs from time series data with perturbations. - Dhananjay Bhaskar; Daniel Sumner Magruder; Edward De Brouwer; Aarthi Venkat; Frederik Wenkel; Guy Wolf; Smita Krishnaswamy (CoRR, 2023)

Graph topological property recovery with heat and wave dynamics-based features on graphs. - Dhananjay Bhaskar; Yanlei Zhang; Charles Xu 004; Xingzhi Sun 003; Oluwadamilola Fasina; Guy Wolf; Maximilian Nickel; Michael Perlmutter; Smita Krishnaswamy (CoRR, 2023)

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. - 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; et al. (CoRR, 2023)

Spectral Temporal Contrastive Learning. - Sacha Morin; Somjit Nath; Samira Ebrahimi Kahou; Guy Wolf (CoRR, 2023)

Multi-view manifold learning of human brain-state trajectories. - Erica L. Busch; Jessie Huang; Andrew Benz; Tom Wallenstein; Guillaume Lajoie; Guy Wolf; Smita Krishnaswamy; Nicholas B. Turk-Browne (Nat. Comput. Sci., 2023)

Geometry Regularized Autoencoders. - Andrés F. Duque; Sacha Morin; Guy Wolf; Kevin R. Moon (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Time-Inhomogeneous Diffusion Geometry and Topology. - Guillaume Huguet; Alexander Tong 001; Bastian Rieck; Jessie Huang; Manik Kuchroo; Matthew J. Hirn; Guy Wolf; Smita Krishnaswamy (SIAM J. Math. Data Sci., 2023)

Understanding Graph Neural Networks with Generalized Geometric Scattering Transforms. - Michael Perlmutter; Alexander Tong 001; Feng Gao; Guy Wolf; Matthew J. Hirn (SIAM J. Math. Data Sci., 2023)

Simulation-Free Schrödinger Bridges via Score and Flow Matching. - Alexander Tong 001; Nikolay Malkin; Kilian Fatras; Lazar Atanackovic; Yanlei Zhang; Guillaume Huguet; Guy Wolf; Yoshua Bengio (AISTATS, 2024)

Non-Uniform Parameter-Wise Model Merging. - Albert Manuel Orozco Camacho; Stefan Horoi; Guy Wolf; Eugene Belilovsky (IEEE Big Data, 2024)

Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy. - Danqi Liao; Chen Liu 020; Benjamin W. Christensen; Alexander Tong 001; Guillaume Huguet; Guy Wolf; Maximilian Nickel; Ian Adelstein; Smita Krishnaswamy (CISS, 2024)

Channel-Selective Normalization for Label-Shift Robust Test-Time Adaptation. - Pedro Vianna; Muawiz Sajjad Chaudhary; Paria Mehrbod; An Tang; Guy Cloutier; Guy Wolf; Michael Eickenberg; Eugene Belilovsky (CoLLAs, 2024)

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. - 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; et al. (ICLR, 2024)

Graph Positional and Structural Encoder. - Semih Cantürk; Renming Liu; Olivier Lapointe-Gagné; Vincent Létourneau; Guy Wolf; Dominique Beaini; Ladislav Rampásek (ICML, 2024)

Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis. - Stefan Horoi; Albert Manuel Orozco Camacho; Eugene Belilovsky; Guy Wolf (ICML, 2024)

Towards a General Recipe for Combinatorial Optimization With Multi-Filter GNNs. - Frederik Wenkel; Semih Cantürk; Stefan Horoi; Michael Perlmutter; Guy Wolf (LoG, 2024)

Enhancing Supervised Visualization Through Autoencoder and Random Forest Proximities for Out-of-Sample Extension. - Shuang Ni; Adrien Aumon; Guy Wolf; Kevin R. Moon; Jake S. Rhodes (MLSP, 2024)

ReactZyme: A Benchmark for Enzyme-Reaction Prediction. - Chenqing Hua; Bozitao Zhong; Sitao Luan; Liang Hong; Guy Wolf; Doina Precup; Shuangjia Zheng (NeurIPS, 2024)

Effective Protein-Protein Interaction Exploration with PPIretrieval. - Chenqing Hua; Connor W. Coley; Guy Wolf; Doina Precup; Shuangjia Zheng (CoRR, 2024)

Towards a General GNN Framework for Combinatorial Optimization. - Frederik Wenkel; Semih Cantürk; Michael Perlmutter; Guy Wolf (CoRR, 2024)

Noisy Data Visualization using Functional Data Analysis. - Haozhe Chen; Andres Felipe Duque Correa; Guy Wolf; Kevin R. Moon (CoRR, 2024)

The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges. - 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 005; et al. (CoRR, 2024)

Are Heterophily-Specific GNNs and Homophily Metrics Really Effective? Evaluation Pitfalls and New Benchmarks. - Sitao Luan; Qincheng Lu; Chenqing Hua; Xinyu Wang; Jiaqi Zhu; Xiao-Wen Chang; Guy Wolf; Jian Tang 005 (CoRR, 2024)

EnzymeFlow: Generating Reaction-specific Enzyme Catalytic Pockets through Flow Matching and Co-Evolutionary Dynamics. - Chenqing Hua; Yong Liu; Dinghuai Zhang; Odin Zhang; Sitao Luan; Kevin K. Yang; Guy Wolf; Doina Precup; Shuangjia Zheng (CoRR, 2024)

Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds. - Xingzhi Sun 003; Danqi Liao; Kincaid MacDonald; Yanlei Zhang; Chen Liu 020; Guillaume Huguet; Guy Wolf; Ian Adelstein; Tim G. J. Rudner; Smita Krishnaswamy (CoRR, 2024)

Reaction-conditioned De Novo Enzyme Design with GENzyme. - Chenqing Hua; Jiarui Lu; Yong Liu; Odin Zhang; Jian Tang 005; Rex Ying; Wengong Jin; Guy Wolf; Doina Precup; Shuangjia Zheng (CoRR, 2024)

Neural networks with optimized single-neuron adaptation uncover biologically plausible regularization. - Victor Geadah; Stefan Horoi; Giancarlo Kerg; Guy Wolf; Guillaume Lajoie (PLoS Comput. Biol., 2024)

Improving and generalizing flow-based generative models with minibatch optimal transport. - Alexander Tong 001; Kilian Fatras; Nikolay Malkin; Guillaume Huguet; Yanlei Zhang; Jarrid Rector-Brooks; Guy Wolf; Yoshua Bengio (Trans. Mach. Learn. Res., 2024)

Learnable Filters for Geometric Scattering Modules. - Alexander Tong 001; Frederik Wenkel; Dhananjay Bhaskar; Kincaid MacDonald; Jackson D. Grady; Michael Perlmutter; Smita Krishnaswamy; Guy Wolf (IEEE Trans. Signal Process., 2024)

Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds. - Xingzhi Sun 003; Danqi Liao; Kincaid MacDonald; Yanlei Zhang; Guillaume Huguet; Guy Wolf; Ian Adelstein; Tim G. J. Rudner; Smita Krishnaswamy (AISTATS, 2025)

Graph Neural Networks Meet Probabilistic Graphical Models: A Survey. - Chenqing Hua; Sitao Luan; Qian Zhang; Jie Fu; Guy Wolf (ICASSP, 2025)

Principal Curvatures Estimation with Applications to Single Cell Data. - Yanlei Zhang; Lydia Mezrag; Xingzhi Sun 003; Charles Xu 004; Kincaid MacDonald; Dhananjay Bhaskar; Smita Krishnaswamy; Guy Wolf; Bastian Rieck (ICASSP, 2025)

AdaFisher: Adaptive Second Order Optimization via Fisher Information. - Damien Martins Gomes; Yanlei Zhang; Eugene Belilovsky; Guy Wolf; Mahdi S. Hosseini (ICLR, 2025)

Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings. - Billy Joe Franks; Moshe Eliasof; Semih Cantürk; Guy Wolf; Carola-Bibiane Schönlieb; Sophie Fellenz; Marius Kloft (Trans. Mach. Learn. Res., 2025)

Random Forest Autoencoders for Guided Representation Learning. - Adrien Aumon; Shuang Ni; Myriam Lizotte; Guy Wolf; Kevin R. Moon; Jake S. Rhodes (CoRR, 2025)

RETRO SYNFLOW: Discrete Flow Matching for Accurate and Diverse Single-Step Retrosynthesis. - Robin Yadav; Qi Yan; Guy Wolf; Avishek Joey Bose; Renjie Liao (CoRR, 2025)

Geometry-Aware Edge Pooling for Graph Neural Networks. - Katharina Limbeck; Lydia Mezrag; Guy Wolf; Bastian Rieck (CoRR, 2025)

Less is More: Undertraining Experts Improves Model Upcycling. - Stefan Horoi; Guy Wolf; Eugene Belilovsky; Gintare Karolina Dziugaite (CoRR, 2025)