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ORCIDMatthew J. Hirn
Person information
- affiliation: Michigan State University, Department of Computational Mathematics, East Lansing, MI, USA
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2020 – today
- 2024
[j7]Liping Yin
, Anna Little, Matthew J. Hirn:
Bispectrum Unbiasing for Dilation-Invariant Multi-Reference Alignment. IEEE Trans. Signal Process. 72: 3761-3775 (2024)- [c12]Holly R. Steach, Siddharth Viswanath, Yixuan He, Xitong Zhang, Natalia Ivanova, Matthew J. Hirn, Michael Perlmutter, Smita Krishnaswamy:
Inferring Metabolic States from Single Cell Transcriptomic Data via Geometric Deep Learning. RECOMB 2024: 235-252 - [i27]Liping Yin, Anna Little, Matthew J. Hirn:
Bispectrum Unbiasing for Dilation-Invariant Multi-reference Alignment. CoRR abs/2402.14276 (2024) - 2023
- [j6]Renming Liu, Matthew J. Hirn, Arjun Krishnan:
Accurately modeling biased random walks on weighted networks using node2vec+. Bioinform. 39(1) (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) - [i26]Sarah McGuire, Elizabeth Munch, Matthew J. Hirn:
NervePool: A Simplicial Pooling Layer. CoRR abs/2305.06315 (2023) - 2022
- [c11]Michael Perlmutter, Jieqian He, Matthew J. Hirn:
Scattering Statistics of Generalized Spatial Poisson Point Processes. ICASSP 2022: 5528-5532 - [c10]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 - [c9]Joyce A. Chew, Holly R. Steach, Siddharth Viswanath, Hau-Tieng Wu, Matthew J. Hirn, Deanna Needell, Matthew D. Vesely, Smita Krishnaswamy, Michael Perlmutter:
The Manifold Scattering Transform for High-Dimensional Point Cloud Data. TAG-ML 2022: 67-78 - [i25]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) - [i24]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) - [i23]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) - [i22]Joyce A. Chew, Holly R. Steach, Siddharth Viswanath, Hau-Tieng Wu, Matthew J. Hirn, Deanna Needell, Smita Krishnaswamy, Michael Perlmutter:
The Manifold Scattering Transform for High-Dimensional Point Cloud Data. CoRR abs/2206.10078 (2022) - [i21]Joyce A. Chew, Matthew J. Hirn, Smita Krishnaswamy, Deanna Needell, Michael Perlmutter, Holly R. Steach, Siddharth Viswanath, Hau-Tieng Wu:
Geometric Scattering on Measure Spaces. CoRR abs/2208.08561 (2022) - 2021
- [j3]Nazanin Donyapour, Matthew J. Hirn, Alex Dickson:
ClassicalGSG: Prediction of logP using classical molecular force fields and geometric scattering for graphs. J. Comput. Chem. 42(14): 1006-1017 (2021) - [c8]Michael Perlmutter, Jieqian He, Mark A. Iwen, Matthew J. Hirn:
A Hybrid Scattering Transform for Signals with Isolated Singularities. ACSCC 2021: 1322-1329 - [c7]Xitong Zhang, Yixuan He, Nathan Brugnone, Michael Perlmutter, Matthew J. Hirn:
MagNet: A Neural Network for Directed Graphs. NeurIPS 2021: 27003-27015 - [i20]Xitong Zhang, Nathan Brugnone, Michael Perlmutter, Matthew J. Hirn:
MagNet: A Magnetic Neural Network for Directed Graphs. CoRR abs/2102.11391 (2021) - [i19]Jieqian He, Matthew J. Hirn:
Texture synthesis via projection onto multiscale, multilayer statistics. CoRR abs/2105.10825 (2021) - [i18]Matthew J. Hirn, Anna Little:
Unbiasing Procedures for Scale-invariant Multi-reference Alignment. CoRR abs/2107.01274 (2021) - [i17]Michael Perlmutter, Jieqian He, Mark A. Iwen, Matthew J. Hirn:
A Hybrid Scattering Transform for Signals with Isolated Singularities. CoRR abs/2110.04910 (2021) - [i16]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) - 2020
- [j2]Mathieu Andreux, Tomás Angles, Georgios Exarchakis, Roberto Leonarduzzi, Gaspar Rochette, Louis Thiry, John Zarka, Stéphane Mallat, Joakim Andén, Eugene Belilovsky, Joan Bruna, Vincent Lostanlen, Muawiz Chaudhary, Matthew J. Hirn, Edouard Oyallon, Sixin Zhang, Carmine-Emanuele Cella, Michael Eickenberg:
Kymatio: Scattering Transforms in Python. J. Mach. Learn. Res. 21: 60:1-60:6 (2020) - [c6]Michael Perlmutter, Feng Gao, Guy Wolf, Matthew J. Hirn:
Geometric Wavelet Scattering Networks on Compact Riemannian Manifolds. MSML 2020: 570-604 - [i15]Paul Sinz, Michael W. Swift, Xavier Brumwell, Jialin Liu, Kwang Jin Kim, Yue Qi, Matthew J. Hirn:
Wavelet Scattering Networks for Atomistic Systems with Extrapolation of Material Properties. CoRR abs/2006.01247 (2020)
2010 – 2019
- 2019
- [c5]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 - [c4]Feng Gao, Guy Wolf, Matthew J. Hirn:
Geometric Scattering for Graph Data Analysis. ICML 2019: 2122-2131 - [i14]Michael Perlmutter, Feng Gao, Guy Wolf, Matthew J. Hirn:
Geometric Wavelet Scattering Networks on Compact Riemannian Manifolds. CoRR abs/1905.10448 (2019) - [i13]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) - [i12]Michael Perlmutter, Feng Gao, Guy Wolf, Matthew J. Hirn:
Understanding Graph Neural Networks with Asymmetric Geometric Scattering Transforms. CoRR abs/1911.06253 (2019) - 2018
- [i11]Michael Eickenberg, Georgios Exarchakis, Matthew J. Hirn, Stéphane Mallat, Louis Thiry:
Solid Harmonic Wavelet Scattering for Predictions of Molecule Properties. CoRR abs/1805.00571 (2018) - [i10]Feng Gao, Guy Wolf, Matthew J. Hirn:
Graph Classification with Geometric Scattering. CoRR abs/1810.03068 (2018) - [i9]Xavier Brumwell, Paul Sinz, Kwang Jin Kim, Yue Qi, Matthew J. Hirn:
Steerable Wavelet Scattering for 3D Atomic Systems with Application to Li-Si Energy Prediction. CoRR abs/1812.02320 (2018) - [i8]Michael Perlmutter, Guy Wolf, Matthew J. Hirn:
Geometric Scattering on Manifolds. CoRR abs/1812.06968 (2018) - [i7]Mathieu Andreux, Tomás Angles, Georgios Exarchakis, Roberto Leonarduzzi, Gaspar Rochette, Louis Thiry, John Zarka, Stéphane Mallat, Joakim Andén, Eugene Belilovsky, Joan Bruna, Vincent Lostanlen, Matthew J. Hirn, Edouard Oyallon, Sixin Zhang, Carmine-Emanuele Cella, Michael Eickenberg:
Kymatio: Scattering Transforms in Python. CoRR abs/1812.11214 (2018) - 2017
- [j1]Matthew J. Hirn, Stéphane Mallat, Nicolas Poilvert:
Wavelet Scattering Regression of Quantum Chemical Energies. Multiscale Model. Simul. 15(2): 827-863 (2017) - [c3]Michael Eickenberg, Georgios Exarchakis, Matthew J. Hirn, Stéphane Mallat:
Solid Harmonic Wavelet Scattering: Predicting Quantum Molecular Energy from Invariant Descriptors of 3D Electronic Densities. NIPS 2017: 6540-6549 - 2016
- [i6]Nicholas F. Marshall, Matthew J. Hirn:
Time Coupled Diffusion Maps. CoRR abs/1608.03628 (2016) - 2015
- [i5]Matthew J. Hirn, Nicolas Poilvert, Stéphane Mallat:
Quantum Energy Regression using Scattering Transforms. CoRR abs/1502.02077 (2015) - 2014
- [i4]Matthew J. Hirn, David P. Widemann:
Frames for subspaces of $\mathbb{C}^N$. CoRR abs/1410.5206 (2014) - [i3]Ariel Herbert-Voss, Matthew J. Hirn, Frederick McCollum:
Computing minimal interpolants in C1, 1(ℝd). CoRR abs/1411.5668 (2014) - 2012
- [c2]Martin Ehler, Matthew J. Hirn:
Sparse endmember extraction and demixing. IGARSS 2012: 1385-1388 - [i2]Ronald R. Coifman, Matthew J. Hirn:
Bi-stochastic kernels via asymmetric affinity functions. CoRR abs/1209.0237 (2012) - [i1]Ronald R. Coifman, Matthew J. Hirn:
Diffusion maps for changing data. CoRR abs/1209.0245 (2012)
2000 – 2009
- 2009
- [c1]John J. Benedetto, Wojciech Czaja, Justin Flake, Matthew J. Hirn:
Frame based Kernel Methods for Automatic Classification in Hyperspectral Data. IGARSS (4) 2009: 697-700
Coauthor Index
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