Publications

Preprints 

4. Graph topological property recovery with heat and wave dynamics-based features on graphs Joint work with D. Bhaskar, Y. Zhang, C. Xu, X. Sun, O. Fasina, G. Wolf, M. Nickel, S. Krishnaswamy: (2023)

3. .  Manifold Filter-Combine Networks - Joint work with J. Chew, Edward de Brouwer, S. Krishnaswamy, D. Needell  (2023)

2. 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 (2023)

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

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 - 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 Papers

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