Preprints
3. HiPoNet: A Topology-Preserving Multi-View Neural Network For High Dimensional Point Cloud and Single-Cell Data Joint work with S. Viswanath, H. Madhu, D. Bhaskar, J. Kovalic, D. Johnson, R. Ying, C. Tape, I. Adelstein, S. Krishnaswamy
2. DYMAG: Rethinking Message Passing Using Dynamical-systems-based Waveforms Joint work with D. Bhaskar, Y. Zhang, C. Xu, X. Sun, O. Fasina, M. Nickel, G. Wolf, S. Krishnaswamy (2024)
1. Overcoming Oversmoothness in Graph Convolutional Networks via Hybrid Scattering Networks - Joint work with F. Wenkel, Y. Min, M. Hirn, and G. Wolf (2022)
Journal Publications
14. Manifold Filter-Combine Networks - Joint work with D. Johnson, J. Chew, Edward de Brouwer, S. Krishnaswamy, D. Needell -Sampling Theory, Signal Processing, and Data Analysis - (2025)
13. Mapping the gene space at single-cell resolution with gene signal pattern analysis - Joint work with A. Venkat, S. Leone, S. E. Youlten, E. Fagerberg, J. Attanasio, N. S. Joshi, S.Krishnaswamy - Nature Computational Sciences, 2024
12. Learnable Filters for Geometric Scattering Modules - Joint work with A. Tong, F. Wenkel, D. Bhaskar, K. Macdonald, J. Grady, S. Krishnaswamy, and G. Wolf - IEEE Transactions on Signal Processing, 2024.
11. Geometric Scattering on Measure Spaces - Joint work with J. Chew, M. Hirn, S. Krishnaswamy, D. Needell, H. Steach, S. Viswanath, H.T. Wu - Applied and Computational Harmonic Analysis (ACHA), 2024
10. Understanding Graph Neural Networks with Generalized Geometric Scattering Transforms - Joint work with F. Gao, A. Tong, G. Wolf, and M. Hirn -SIAM Journal on Mathematics of Data Science (SIMODS) 2023
9. Modewise Operators, the Tensor Restricted Isometry Property, and Low-Rank Tensor Recovery - Joint work with M. Iwen, D. Needell, and E. Rebrova - Applied and Computational Harmonic Analysis (ACHA) 2023
8. Multi-scale Hybridized Topic Modeling: A Pipeline for analyzing unstructured text datasets via Topic Modeling - Joint work with K. Cheng, S Inzer, A. Leung, Xiaoxian Shen, J. Chew, M. Lindstrom, D. Needell, T. Presner - SIAM Undergraduate Research Online (SIURO), 2023
7. Toward Fast and Provably Accurate Near-field Ptychographic Phase Retrieval - Joint Work with M. Roach, and M. Iwen - Sampling Theory, Signal Processing, and Data Analysis, 2023
6. Phase Retrieval for L2([−π,π]) via the Provably Accurate and Noise Robust Numerical Inversion of Spectrogram Measurements - Joint work with M. Iwen, N. Sissouno, and A. Viswanathan - Journal of Fourier Analysis and Applications (JFAA), 2022
5. Inverting Spectorgram Measurements via Aliased Wigner Distribution Deconvolution and Angular Synchronization -Joint work with S. Merhi, A. Viswanathan, and M. Iwen - Information and Inference: A Journal of the IMA, 2020
4. A New Approach to Large Deviations for the Ginzburg-Landau Model - Joint work with S. Banerjee and A. Budhiraja - Electronic Journal of Probability, 2020
3. Lower Lipschitz Bounds for Phase Retrieval from Locally Supported Measurements - Joint work with M. Iwen and S. Merhi - Applied and Computational Harmonic Analysis (ACHA), 2019
2. A Method of Rotations for Lévy Multipliers – Mathematische Zeitschrift, 2017
1. On a Class of Calderón-Zygmund Operators Arising from Projections of Martingale Transforms – Potential Analysis, 2015
Conference and Workshop Papers
26. Hyperedge Representations with Hypergraph Wavelets: Applications to Spatial Transcriptomics Hyperedge Representations with Hypergraph Wavelets: Applications to Spatial Transcriptomics Joint work with Xingzhi Sun, Charles Xu, Joao F. Rocha, Chen Liu, Benjamin Hollander-Bodie, Laney Goldman, Marcello DiStasio, S. Krishnaswamy International Conference on Acoustics, Speech, & Signal Processing (ICASSP) (2024)
25. Towards a General GNN Framework for Combinatorial Optimization Towards a General GNN Recipe for Combinatorial Optimization Joint work with F. Wenkel, S. Canturk, S. Horoi, M. Perlmutter, G. Wolf: Towards a General GNN Framework for Combinatorial Optimization Learning on Graphs conference (LoG), (2024)
24. Convergence of Manifold Filter-Combine Networks - Joint work with D. Johnson, J. Chew, S. Viswanath, E. De Brouwer, D. Needell, S. Krishnaswamy - NeurIPS Symmetry and Geometry in Neural Representations workshop (2024)
23. Mapping the landscape of protein conformations in molecular dynamics - Joint work with S. Viswanath, D. Bhaskar, D. Johnson, J. Felipe Rocha, E. Castro, J. Grady, A. Grigas, C. O'Hern, S. Krishnaswamy - Molecular Machine Learning Conference (MoML) (2024)
22. Directed Scattering for Knowledge Graph-based Cellular Signaling Analysis - Joint work with A. Venkat, J. Chew, F. Cardoso Rodriguez, C. J. Tape, S. Krishnaswamy- International Conference on Acoustics, Speech, & Signal Processing (ICASSP) (2024)
21. Inferring Metabolic States from Single Cell Transcriptomic Data via Geometric Deep Learning - Joint work with H. Steach, S. Viswanath, Y. He, X. Zhange, N. Ivanova, M. Hirn, S. Krishnaswamy - Research in Computational Molecular Biology (RECOMB) (2024)
20. BLIS-Net: Classifying and Analyzing Signals on Graphs - Joint work with C. Xu, L. Goldman, V. Guo, B. Hollander-Bodie, M., I. Adelstein, E. De Brouwer, R. Ying, S.Krishnaswamy - Artificial Intelligence and Statistics (AISTATS) (2024)
19. Bayesian Formulations for Graph Spectral Denoising - Joint work with S. Leone, X. Sun, S. Krishnaswamy: Conference on Information Sciences and Systems (CISS) (2024)
18. Learning directed and hyperbolic gene embeddings - Joint work with A. Venkat, F. Rodriguez, J. Chew, C. Tape, S. Krishnaswamy: Graph Signal Processing Workshop (2023)
17. Wire Before You Walk - Joint work with T. Asmara, D. Bhaskar, I. Adelstein, S. Krishnaswamy:Asilomar Conference on Signals, Systems, and Computers (2023).
16. A Flow Artist for High-Dimensional Cellular Data - Joint work with K. MacDonald, D. Bhakar, G. Thampakkul, N. Nguyen, J. Zhang, I. Adelstein, S.Krishnaswamy- IEEE International Workshop on Machine Learning for Signal Processing (MLSP) (2023)
15. A Convergence Rate for Manifold Neural Networks - Joint work with J. Chew and D. Needell -SAMPTA 2023
14. MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian - Joint Work with Y. He, G. Reinert, M. Cucuringu - Learning on Graphs conference (LoG), 2022
13. 6. Taxonomy of Benchmarks in Graph Representation Learning - Joint Work with R. Liu, S. Canturk, F. Wenkel, S. McGuire, E. Wang, A. Little, L. O'Bray, B. Rieck, M. Hirn, G. Wolf, L. Rampavsek - Learning on Graphs conference (LoG), 2022
12. Can Hybrid Geometric Scattering Networks Help Solve the Maximal Clique Problem? - Joint Work with F. Wenkel, Y. Min, G. Wolf - Neural Information Processing Symposium (NeurIPS), 2022.
11. Molecular Graph Generation via Geometric Scattering - Joint work with D. Bhaskar, J. Grady, and S. Krishnaswamy - IEEE Workshop on Machine Learning for Signal Processing (MLSP), 2022
10. The Manifold Scattering Transform for High-Dimensional Point Cloud Data - Joint work with J. Chew, H. Steach, S. Viswanath, H.T. Wu, M. Hirn, D. Needell, S. Krishnaswamy - ICML Workshop on Topology Algebra and Geometry in Machine Learning, 2022
9. On audio enhancement via online non-negative matrix factorization - Joint work with A. Sack, W. Jiang, P. Salanevich, and D. Needell - CISS 2022
8. Scattering Statistics of Generalized Spatial Poisson Point Processes - Joint work with J. He and M. Hirn - ICASSP 2022
7, Towards a Taxonomy of Graph Learning Datasets - Joint work with R. Liu, S. Canturk, F. Wenkel, D. Sandfelder, D. Kreuzer, A. Little, S. McGuire, L. O'Bray, B. Rieck, M. Hirn, G. Wolf, L. Rampasek - Neural Information Processing Symposium (NeurIPS) Data-Centric AI workshop, 2021
6. MagNet: A Neural Network for Directed Graphs - Joint work with X. Zhang, Y. He, N. Brugnone, and M. Hirn: Neural Information Processing Symposium (NeurIPS), 2021.
5. A Hybrid Scattering Transform for Signals with Isolated Singularities - Joint work with J. He, M. Iwen, and M. Hirn - Asilomar Conference on Signals, Systems, and Computers, 2021
4. Geometric Wavelet Scattering Networks on Compact Riemannian Manifolds - Joint work with M. Hirn and G. Wolf - MSML, 2020
3. A Provably Accurate Algorithm for Recovering Compactly Supported Smooth Functions From Spectrogram Measurements - Joint work with N. Sissouno, A. Viswanathan, and M. Iwen - EUSIPCO, 2020
2. Geometric Scattering on Manifolds - Joint work with G. Wolf and M. Hirn - NeurIPS Integration of Deep Learning theories workshop, 2019
1. Geometric Wavelet Scattering on Graphs and Manifolds- Joint work with F. Gao, M. Hirn, and G. Wolf - Proceedings of SPIE, Wavelets and Sparsity XVIII, vol. 10394, 2019