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2020 – today
- 2024
[j9]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)- [j8]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: 2939-2952 (2024) - [c49]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: 1279-1287 - [c48]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: 1-6 - [c47]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 - [c46]Semih Cantürk, Renming Liu, Olivier Lapointe-Gagné, Vincent Létourneau, Guy Wolf, Dominique Beaini, Ladislav Rampásek:
Graph Positional and Structural Encoder. ICML 2024 - [c45]Stefan Horoi, Albert Manuel Orozco Camacho, Eugene Belilovsky, Guy Wolf:
Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis. ICML 2024 - [i69]Chenqing Hua, Connor W. Coley, Guy Wolf, Doina Precup, Shuangjia Zheng:
Effective Protein-Protein Interaction Exploration with PPIretrieval. CoRR abs/2402.03675 (2024) - [i68]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 abs/2402.04958 (2024) - [i67]Damien Martins Gomes, Yanlei Zhang, Eugene Belilovsky, Guy Wolf, Mahdi S. Hosseini:
AdaFisher: Adaptive Second Order Optimization via Fisher Information. CoRR abs/2405.16397 (2024) - [i66]Frederik Wenkel, Semih Cantürk, Michael Perlmutter, Guy Wolf:
Towards a General GNN Framework for Combinatorial Optimization. CoRR abs/2405.20543 (2024) - [i65]Haozhe Chen, Andres Felipe Duque Correa, Guy Wolf, Kevin R. Moon:
Noisy Data Visualization using Functional Data Analysis. CoRR abs/2406.03396 (2024) - [i64]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 abs/2406.04421 (2024) - [i63]Stefan Horoi, Albert Manuel Orozco Camacho, Eugene Belilovsky, Guy Wolf:
Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis. CoRR abs/2407.05385 (2024) - [i62]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 abs/2407.09618 (2024) - [i61]Chenqing Hua, Bozitao Zhong, Sitao Luan, Liang Hong, Guy Wolf, Doina Precup, Shuangjia Zheng:
Reactzyme: A Benchmark for Enzyme-Reaction Prediction. CoRR abs/2408.13659 (2024) - [i60]Sitao Luan, Qincheng Lu, Chenqing Hua, Xinyu Wang, Jiaqi Zhu, Xiao-Wen Chang, Guy Wolf, Jian Tang:
Are Heterophily-Specific GNNs and Homophily Metrics Really Effective? Evaluation Pitfalls and New Benchmarks. CoRR abs/2409.05755 (2024) - [i59]Chenqing Hua, Yong Liu, Dinghuai Zhang, Odin Zhang, Sitao Luan, Kevin K. Yang, Guy Wolf, Doina Precup, Shuangjia Zheng:
EnzymeFlow: Generating Reaction-specific Enzyme Catalytic Pockets through Flow Matching and Co-Evolutionary Dynamics. CoRR abs/2410.00327 (2024) - 2023
- [j7]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): 240-253 (2023) - [j6]Andrés F. Duque, Sacha Morin, Guy Wolf, Kevin R. Moon:
Geometry Regularized Autoencoders. IEEE Trans. Pattern Anal. Mach. Intell. 45(6): 7381-7394 (2023) - [j5]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): 346-372 (2023) - [j4]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): 873-898 (2023) - [c44]Mostafa ElAraby, Guy Wolf, Margarida Carvalho:
OAMIP: Optimizing ANN Architectures Using Mixed-Integer Programming. CPAIOR 2023: 219-237 - [c43]MohammadReza Davari, Stefan Horoi, Amine Natik, Guillaume Lajoie, Guy Wolf, Eugene Belilovsky:
Reliability of CKA as a Similarity Measure in Deep Learning. ICLR 2023 - [c42]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: 9814-9826 - [c41]Andrés F. Duque, Guy Wolf, Kevin R. Moon:
Diffusion Transport Alignment. IDA 2023: 116-129 - [c40]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: 22 - [c39]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: 1-6 - [c38]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 - [i58]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 abs/2302.00482 (2023) - [i57]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 abs/2305.19043 (2023) - [i56]Samuel Leone, Aarthi Venkat, Guillaume Huguet, Alexander Tong, Guy Wolf, Smita Krishnaswamy:
Graph Fourier MMD for Signals on Graphs. CoRR abs/2306.02508 (2023) - [i55]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 abs/2306.06062 (2023) - [i54]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 abs/2306.07803 (2023) - [i53]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 abs/2307.03672 (2023) - [i52]Renming Liu, Semih Cantürk, Olivier Lapointe-Gagné, Vincent Létourneau, Guy Wolf, Dominique Beaini, Ladislav Rampásek:
Graph Positional and Structural Encoder. CoRR abs/2307.07107 (2023) - [i51]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 abs/2309.09924 (2023) - [i50]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 abs/2310.04292 (2023) - [i49]Sacha Morin, Somjit Nath, Samira Ebrahimi Kahou, Guy Wolf:
Spectral Temporal Contrastive Learning. CoRR abs/2312.00966 (2023) - [i48]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 abs/2312.04823 (2023) - 2022
- [j3]Alexander Tong, Guy Wolf, Smita Krishnaswamy:
Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators. J. Signal Process. Syst. 94(2): 229-243 (2022) - [c37]Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Muawiz Chaudhary, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf:
Parametric Scattering Networks. CVPR 2022: 5739-5748 - [c36]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: 5647-5651 - [c35]Stefan Horoi, Jessie Huang, Bastian Rieck, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy:
Exploring the Geometry and Topology of Neural Network Loss Landscapes. IDA 2022: 171-184 - [c34]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: 6 - [c33]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: 1-6 - [c32]Vijay Prakash Dwivedi, Ladislav Rampásek, Michael Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini:
Long Range Graph Benchmark. NeurIPS 2022 - [c31]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 - [c30]Yimeng Min, Frederik Wenkel, Michael Perlmutter, Guy Wolf:
Can Hybrid Geometric Scattering Networks Help Solve the Maximum Clique Problem? NeurIPS 2022 - [c29]Ladislav Rampásek, Michael Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini:
Recipe for a General, Powerful, Scalable Graph Transformer. NeurIPS 2022 - [c28]Alexander Cloninger, Timothy Doster, Tegan Emerson, Manohar Kaul, Ira Ktena, Henry Kvinge, Nina Miolane, Bastian Rice, Sarah Tymochko, Guy Wolf:
Preface. TAG-ML 2022: 1-5 - [e1]Alexander Cloninger, Timothy Doster, Tegan Emerson, Manohar Kaul, Ira Ktena, Henry Kvinge, Nina Miolane, Bastian Rice, Sarah Tymochko, Guy Wolf:
Topological, Algebraic and Geometric Learning Workshops 2022, 25-22 July 2022, Virtual. Proceedings of Machine Learning Research 196, PMLR 2022 [contents] - [i47]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 abs/2201.00622 (2022) - [i46]Frederik Wenkel, Yimeng Min, Matthew J. Hirn, Michael Perlmutter, Guy Wolf:
Overcoming Oversmoothness in Graph Convolutional Networks via Hybrid Scattering Networks. CoRR abs/2201.08932 (2022) - [i45]Guillaume Huguet, Alexander Tong, Bastian Rieck, Jessie Huang, Manik Kuchroo, Matthew J. Hirn, Guy Wolf, Smita Krishnaswamy:
Time-inhomogeneous diffusion geometry and topology. CoRR abs/2203.14860 (2022) - [i44]Ladislav Rampásek, Mikhail Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini:
Recipe for a General, Powerful, Scalable Graph Transformer. CoRR abs/2205.12454 (2022) - [i43]Yimeng Min, Frederik Wenkel, Michael Perlmutter, Guy Wolf:
Can Hybrid Geometric Scattering Networks Help Solve the Maximal Clique Problem? CoRR abs/2206.01506 (2022) - [i42]Andrés F. Duque, Guy Wolf, Kevin R. Moon:
Diffusion Transport Alignment. CoRR abs/2206.07305 (2022) - [i41]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 abs/2206.07729 (2022) - [i40]Vijay Prakash Dwivedi, Ladislav Rampásek, Mikhail Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini:
Long Range Graph Benchmark. CoRR abs/2206.08164 (2022) - [i39]Guillaume Huguet, Daniel Sumner Magruder, Oluwadamilola Fasina, Alexander Tong, Manik Kuchroo, Guy Wolf, Smita Krishnaswamy:
Manifold Interpolating Optimal-Transport Flows for Trajectory Inference. CoRR abs/2206.14928 (2022) - [i38]Alexander Tong, Frederik Wenkel, Dhananjay Bhaskar, Kincaid MacDonald, Jackson D. Grady, Michael Perlmutter, Smita Krishnaswamy, Guy Wolf:
Learnable Filters for Geometric Scattering Modules. CoRR abs/2208.07458 (2022) - [i37]Andrés F. Duque, Myriam Lizotte, Guy Wolf, Kevin R. Moon:
Manifold Alignment with Label Information. CoRR abs/2210.12774 (2022) - [i36]MohammadReza Davari, Stefan Horoi, Amine Natik, Guillaume Lajoie, Guy Wolf, Eugene Belilovsky:
Reliability of CKA as a Similarity Measure in Deep Learning. CoRR abs/2210.16156 (2022) - [i35]Guillaume Huguet, Alexander Tong, María Ramos Zapatero, Guy Wolf, Smita Krishnaswamy:
Geodesic Sinkhorn: optimal transport for high-dimensional datasets. CoRR abs/2211.00805 (2022) - 2021
- [c27]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: 4694-4704 - [c26]Yimeng Min, Frederik Wenkel, Guy Wolf:
Geometric Scattering Attention Networks. ICASSP 2021: 8518-8522 - [c25]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: 10336-10346 - [c24]Manik Kuchroo, Abhinav Godavarthi, Alexander Tong, Guy Wolf, Smita Krishnaswamy:
Multimodal Data Visualization and Denoising with Integrated Diffusion. MLSP 2021: 1-6 - [c23]Ladislav Rampásek, Guy Wolf:
Hierarchical Graph Neural Nets can Capture Long-Range Interactions. MLSP 2021: 1-6 - [c22]Alexander Tong, Frederick Wenkel, Kincaid MacDonald, Smita Krishnaswamy, Guy Wolf:
Data-Driven Learning of Geometric Scattering Modules for GNNs. MLSP 2021: 1-6 - [c21]Jake S. Rhodes, Adele Cutler, Guy Wolf, Kevin R. Moon:
Random Forest-Based Diffusion Information Geometry for Supervised Visualization and Data Exploration. SSP 2021: 331-335 - [i34]Stefan Horoi, Jessie Huang, Guy Wolf, Smita Krishnaswamy:
Visualizing High-Dimensional Trajectories on the Loss-Landscape of ANNs. CoRR abs/2102.00485 (2021) - [i33]Manik Kuchroo, Abhinav Godavarthi, Guy Wolf, Smita Krishnaswamy:
Multimodal data visualization, denoising and clustering with integrated diffusion. CoRR abs/2102.06757 (2021) - [i32]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 abs/2102.12833 (2021) - [i31]Ladislav Rampásek, Guy Wolf:
Hierarchical graph neural nets can capture long-range interactions. CoRR abs/2107.07432 (2021) - [i30]Shanel Gauthier, Benjamin Thérien, Laurent Alsène-Racicot, Irina Rish, Eugene Belilovsky, Michael Eickenberg, Guy Wolf:
Parametric Scattering Networks. CoRR abs/2107.09539 (2021) - [i29]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 abs/2107.12334 (2021) - [i28]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:
Towards a Taxonomy of Graph Learning Datasets. CoRR abs/2110.14809 (2021) - [i27]Guy Wolf, Gil Shabat, Hanan Shteingart:
Positivity Validation Detection and Explainability via Zero Fraction Multi-Hypothesis Testing and Asymmetrically Pruned Decision Trees. CoRR abs/2111.04033 (2021) - [i26]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 abs/2111.10452 (2021) - 2020
- [c20]Stefan Horoi, Victor Geadah, Guy Wolf, Guillaume Lajoie:
Low-Dimensional Dynamics of Encoding and Learning in Recurrent Neural Networks. Canadian AI 2020: 276-282 - [c19]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: 4519-4528 - [c18]Andrés F. Duque, Sacha Morin, Guy Wolf, Kevin R. Moon:
Extendable and invertible manifold learning with geometry regularized autoencoders. IEEE BigData 2020: 5027-5036 - [c17]Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy:
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. ICML 2020: 9526-9536 - [c16]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: 509-521 - [c15]Alexander Tong, Guy Wolf, Smita Krishnaswamy:
Fixing Bias in Reconstruction-Based Anomaly Detection with Lipschitz Discriminators. MLSP 2020: 1-6 - [c14]Matthew Amodio, David van Dijk, Guy Wolf, Smita Krishnaswamy:
Learning General Transformations of Data for Out-of-Sample Extensions. MLSP 2020: 1-6 - [c13]Michael Perlmutter, Feng Gao, Guy Wolf, Matthew J. Hirn:
Geometric Wavelet Scattering Networks on Compact Riemannian Manifolds. MSML 2020: 570-604 - [c12]Yimeng Min, Frederik Wenkel, Guy Wolf:
Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks. NeurIPS 2020 - [c11]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 - [c10]Jay S. Stanley III, Scott Gigante, Guy Wolf, Smita Krishnaswamy:
Harmonic Alignment. SDM 2020: 316-324 - [i25]Stefan Horoi, Guillaume Lajoie, Guy Wolf:
Internal representation dynamics and geometry in recurrent neural networks. CoRR abs/2001.03255 (2020) - [i24]Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy:
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. CoRR abs/2002.04461 (2020) - [i23]Mostafa ElAraby, Guy Wolf, Margarida Carvalho:
Identifying Critical Neurons in ANN Architectures using Mixed Integer Programming. CoRR abs/2002.07259 (2020) - [i22]Yimeng Min, Frederik Wenkel, Guy Wolf:
Scattering GCN: Overcoming Oversmoothness in Graph Convolutional Networks. CoRR abs/2003.08414 (2020) - [i21]Egbert Castro, Andrew Benz, Alexander Tong, Guy Wolf, Smita Krishnaswamy:
Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings. CoRR abs/2006.06885 (2020) - [i20]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 abs/2006.07882 (2020) - [i19]Jake S. Rhodes, Adele Cutler, Guy Wolf, Kevin R. Moon:
Supervised Visualization for Data Exploration. CoRR abs/2006.08701 (2020) - [i18]Victor Geadah, Giancarlo Kerg, Stefan Horoi, Guy Wolf, Guillaume Lajoie:
Advantages of biologically-inspired adaptive neural activation in RNNs during learning. CoRR abs/2006.12253 (2020) - [i17]Andrés F. Duque, Sacha Morin, Guy Wolf, Kevin R. Moon:
Extendable and invertible manifold learning with geometry regularized autoencoders. CoRR abs/2007.07142 (2020) - [i16]Alexander Tong, Frederik Wenkel, Kincaid MacDonald, Smita Krishnaswamy, Guy Wolf:
Data-Driven Learning of Geometric Scattering Networks. CoRR abs/2010.02415 (2020) - [i15]Yimeng Min, Frederik Wenkel, Guy Wolf:
Geometric Scattering Attention Networks. CoRR abs/2010.15010 (2020)
2010 – 2019
- 2019
- [c9]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: 2624-2633 - [c8]David van Dijk, Daniel B. Burkhardt, Matthew Amodio, Alexander Tong, Guy Wolf, Smita Krishnaswamy:
Finding Archetypal Spaces Using Neural Networks. IEEE BigData 2019: 2634-2643 - [c7]Daniel B. Burkhardt, Jay S. Stanley III, Guy Wolf, Smita Krishnaswamy:
Vertex-Frequency Clustering. DSW 2019: 145-149 - [c6]Feng Gao, Guy Wolf, Matthew J. Hirn:
Geometric Scattering for Graph Data Analysis. ICML 2019: 2122-2131 - [c5]Andrés F. Duque, Guy Wolf, Kevin R. Moon:
Visualizing High Dimensional Dynamical Processes. MLSP 2019: 1-6 - [i14]David van Dijk, Daniel B. Burkhardt, Matthew Amodio, Alexander Tong, Guy Wolf, Smita Krishnaswamy:
Finding Archetypal Spaces for Data Using Neural Networks. CoRR abs/1901.09078 (2019) - [i13]Scott Gigante, Jay S. Stanley III, Ngan Vu, David van Dijk, Kevin R. Moon, Guy Wolf, Smita Krishnaswamy:
Compressed Diffusion. CoRR abs/1902.00033 (2019) - [i12]Michael Perlmutter, Feng Gao, Guy Wolf, Matthew J. Hirn:
Geometric Wavelet Scattering Networks on Compact Riemannian Manifolds. CoRR abs/1905.10448 (2019) - [i11]Alexander Tong, Guy Wolf, Smita Krishnaswamy:
A Lipschitz-constrained anomaly discriminator framework. CoRR abs/1905.10710 (2019) - [i10]Andrés F. Duque, Guy Wolf, Kevin R. Moon:
Visualizing High Dimensional Dynamical Processes. CoRR abs/1906.10725 (2019) - [i9]Nathan Brugnone, Alex Gonopolskiy, Mark W. Moyle, Manik Kuchroo, David van Dijk, Kevin R. Moon, Daniel Colón-Ramos, Guy Wolf, Matthew J. Hirn, Smita Krishnaswamy:
Coarse Graining of Data via Inhomogeneous Diffusion Condensation. CoRR abs/1907.04463 (2019) - [i8]Michael Perlmutter, Feng Gao, Guy Wolf, Matthew J. Hirn:
Understanding Graph Neural Networks with Asymmetric Geometric Scattering Transforms. CoRR abs/1911.06253 (2019) - 2018
- [c4]Ofir Lindenbaum, Jay S. Stanley III, Guy Wolf, Smita Krishnaswamy:
Geometry Based Data Generation. NeurIPS 2018: 1407-1418 - [i7]David van Dijk, Scott Gigante, Alexander Strzalkowski, Guy Wolf, Smita Krishnaswamy:
Modeling Dynamics with Deep Transition-Learning Networks. CoRR abs/1802.03497 (2018) - [i6]Ofir Lindenbaum, Jay S. Stanley III, Guy Wolf, Smita Krishnaswamy:
Geometry-Based Data Generation. CoRR abs/1802.04927 (2018) - [i5]Jay S. Stanley III, Guy Wolf, Smita Krishnaswamy:
Manifold Alignment with Feature Correspondence. CoRR abs/1810.00386 (2018) - [i4]Alexander Tong, David van Dijk, Jay S. Stanley III, Matthew Amodio, Guy Wolf, Smita Krishnaswamy:
Graph Spectral Regularization for Neural Network Interpretability. CoRR abs/1810.00424 (2018) - [i3]Feng Gao, Guy Wolf, Matthew J. Hirn:
Graph Classification with Geometric Scattering. CoRR abs/1810.03068 (2018) - [i2]Michael Perlmutter, Guy Wolf, Matthew J. Hirn:
Geometric Scattering on Manifolds. CoRR abs/1812.06968 (2018) - 2016
- [j2]Moshe Salhov, Amit Bermanis, Guy Wolf, Amir Averbuch:
Learning from patches by efficient spectral decomposition of a structured kernel. Mach. Learn. 103(1): 81-102 (2016) - [j1]Guy Wolf, Stéphane Mallat, Shihab A. Shamma:
Rigid Motion Model for Audio Source Separation. IEEE Trans. Signal Process. 64(7): 1822-1831 (2016) - 2015
- [i1]Moshe Salhov, Amit Bermanis, Guy Wolf, Amir Averbuch:
Diffusion Representations. CoRR abs/1511.06208 (2015) - 2014
- [c3]Guy Wolf, Stéphane Mallat, Shihab A. Shamma:
Audio source separation with time-frequency velocities. MLSP 2014: 1-6 - [p1]Guy Wolf, Amir Averbuch, Pekka Neittaanmäki:
Parameter Rating by Diffusion Gradient. Modeling, Simulation and Optimization for Science and Technology 2014: 225-248 - 2013
- [b1]Guy Wolf:
Diffusion-based analysis of locally low-dimensional geometries in high-dimensional data. Tel Aviv University, Israel, 2013 - 2012
- [c2]Moshe Salhov, Guy Wolf, Amir Averbuch, Pekka Neittaanmäki:
Patch-Based Data Analysis Using Linear-Projection Diffusion. IDA 2012: 334-345 - [c1]Moshe Salhov, Guy Wolf, Amit Bermanis, Amir Averbuch, Pekka Neittaanmäki:
Dictionary Construction for Patch-to-Tensor Embedding. IDA 2012: 346-356
Coauthor Index
[j8] [c48] [j7] [j5] [c42] [c40] [c39] [c38] [i57] [i56] [i55] [i54] [i51] [i48] [j3] [c36] [c35] [c33] [c31] [i47] [i45] [i39] [i38] [i35] [c27] [c25] [c24] [c22] [i34] [i33] [i32] [i29] [i26] [c19] [c17] [c16] [c15] [c14] [c11] [c10] [i24] [i21] [i20] [i16] [c9] [c8] [c7] [i14] [i13] [i11] [i9] [c4] [i7] [i6] [i5] [i4]
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