Smita Krishnaswamy

148 papers A* 16A 8B 7Misc 10Journal 85Unranked 19

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Dispersion Loss Counteracts Embedding Condensation and Improves Generalization in Small Language Models. CoRR Chen Liu, Xingzhi Sun, Xi Xiao, Alexandre Van Tassel, Ke Xu, Kristof Reimann, Danqi Liao, Mark Gerstein, Tianyang Wang, Xiao Wang, Smita Krishnaswamy
2026	J	`jnl`	HypRAG: Hyperbolic Dense Retrieval for Retrieval Augmented Generation. CoRR Hiren Madhu, Ngoc Bui, Ali Maatouk, Leandros Tassiulas, Smita Krishnaswamy, Menglin Yang, Sukanta Ganguly, Kiran Srinivasan, Rex Ying
2026	J	`jnl`	MIOFlow 2.0: A unified framework for inferring cellular stochastic dynamics from single cell and spatial transcriptomics data. CoRR Xingzhi Sun, João F. Rocha, Brett Phelan, Dhananjay Bhaskar, Guillaume Huguet, Yanlei Zhang, Daniel Sumner Magruder, Alexander Tong, Ke Xu, Oluwadamilola Fasina, Mark Gerstein, Guy Wolf, Natalia Ivanova, Christine L. Chaffer, Smita Krishnaswamy
2025	J	`jnl`	CTR-LoRA: Curvature-Aware and Trust-Region Guided Low-Rank Adaptation for Large Language Models. CoRR Zhuxuanzi Wang, Mingqiao Mo, Xi Xiao, Chen Liu, Chenrui Ma, Yunbei Zhang, Xiao Wang, Smita Krishnaswamy, Tianyang Wang
2025	J	`jnl`	CellForge: Agentic Design of Virtual Cell Models. CoRR Xiangru Tang, Zhuoyun Yu, Jiapeng Chen, Yan Cui, Daniel Shao, Weixu Wang, Fang Wu, Yuchen Zhuang, Wenqi Shi, Zhi Huang, Arman Cohan, Xihong Lin, Fabian J. Theis, Smita Krishnaswamy, Mark Gerstein
2025	Misc	`conf`	DiffKillR: Killing and Recreating Diffeomorphisms for Cell Annotation in Dense Microscopy Images. ICASSP Chen Liu, Danqi Liao, Alejandro Parada-Mayorga, Alejandro Ribeiro, Marcello DiStasio, Smita Krishnaswamy
2025	J	`jnl`	Equivariant Geometric Scattering Networks via Vector Diffusion Wavelets. CoRR David R. Johnson, Rishabh Anand, Smita Krishnaswamy, Michael Perlmutter
2025	A	`conf`	Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds. AISTATS Xingzhi Sun, Danqi Liao, Kincaid MacDonald, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Ian Adelstein, Tim G. J. Rudner, Smita Krishnaswamy
2025	J	`jnl`	HEIST: A Graph Foundation Model for Spatial Transcriptomics and Proteomics Data. CoRR Hiren Madhu, João F. Rocha, Tinglin Huang, Siddharth Viswanath, Smita Krishnaswamy, Rex Ying
2025	J	`jnl`	HELM: Hyperbolic Large Language Models via Mixture-of-Curvature Experts. CoRR Neil He, Rishabh Anand, Hiren Madhu, Ali Maatouk, Smita Krishnaswamy, Leandros Tassiulas, Menglin Yang, Rex Ying
2025	J	`jnl`	HiPoNet: A Topology-Preserving Multi-View Neural Network For High Dimensional Point Cloud and Single-Cell Data. CoRR Siddharth Viswanath, Hiren Madhu, Dhananjay Bhaskar, Jake Kovalic, David R. Johnson, Rex Ying, Christopher J. Tape, Ian Adelstein, Michael Perlmutter, Smita Krishnaswamy
2025	Misc	`conf`	Hyperedge Representations with Hypergraph Wavelets: Applications to Spatial Transcriptomics. ICASSP Xingzhi Sun, Charles Xu, João F. Rocha, Chen Liu, Benjamin Hollander-Bodie, Laney Goldman, Marcello DiStasio, Michael Perlmutter, Smita Krishnaswamy
2025	Misc	`conf`	ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images. ICASSP Chen Liu, Ke Xu, Liangbo L. Shen, Guillaume Huguet, Zilong Wang, Alexander Tong, Danilo Bzdok, Jay Stewart, Jay C. Wang, Luciano V. Del Priore, Smita Krishnaswamy
2025	J	`jnl`	InfoGain Wavelets: Furthering the Design of Diffusion Wavelets for Graph-Structured Data. CoRR David R. Johnson, Smita Krishnaswamy, Michael Perlmutter
2025	Misc	`conf`	Latent Representation Learning for Multimodal Brain Activity Translation. ICASSP Arman Afrasiyabi, Dhananjay Bhaskar, Erica L. Busch, Laurent Caplette, Rahul Singh, Guillaume Lajoie, Nicholas B. Turk-Browne, Smita Krishnaswamy
2025	J	`jnl`	Learning Laplacian Eigenvectors: a Pre-training Method for Graph Neural Networks. CoRR Howard Dai, Nyambura Njenga, Benjamin Whitsett, Catherine Ma, Darwin Deng, Sara de Ángel, Alexandre Van Tassel, Siddharth Viswanath, Ryan Pellico, Ian Adelstein, Smita Krishnaswamy
2025	J	`jnl`	Linearized Optimal Transport for Analysis of High-Dimensional Point-Cloud and Single-Cell Data. CoRR Tianxiang Wang, Yingtong Ke, Dhananjay Bhaskar, Smita Krishnaswamy, Alexander Cloninger
2025	J	`jnl`	Low-dimensional embeddings of high-dimensional data. CoRR Cyril de Bodt, Alex Diaz-Papkovich, Michael Bleher, Kerstin Bunte, Corinna Coupette, Sebastian Damrich, Enrique Fita Sanmartin, Fred A. Hamprecht, Emoke-Ágnes Horvát, Dhruv Kohli, Smita Krishnaswamy, John A. Lee, Boudewijn P. F. Lelieveldt, Leland McInnes, Ian T. Nabney, Maximilian Noichl, Pavlin G. Policar, Bastian Rieck, Guy Wolf, Gal Mishne, Dmitry Kobak
2025	Misc	`conf`	Principal Curvatures Estimation with Applications to Single Cell Data. ICASSP Yanlei Zhang, Lydia Mezrag, Xingzhi Sun, Charles Xu, Kincaid MacDonald, Dhananjay Bhaskar, Smita Krishnaswamy, Guy Wolf, Bastian Rieck
2025	J	`jnl`	Principal Curvatures Estimation with Applications to Single Cell Data. CoRR Yanlei Zhang, Lydia Mezrag, Xingzhi Sun, Charles Xu, Kincaid MacDonald, Dhananjay Bhaskar, Smita Krishnaswamy, Guy Wolf, Bastian Rieck
2025	J	`jnl`	RNAGenScape: Property-guided Optimization and Interpolation of mRNA Sequences with Manifold Langevin Dynamics. CoRR Danqi Liao, Chen Liu, Xingzhi Sun, Dié Tang, Haochen Wang, Scott E. Youlten, Srikar Krishna Gopinath, Haejeong Lee, Ethan C. Strayer, Antonio J. Giraldez, Smita Krishnaswamy
2025	—	`conf`	STAGED: A Multi-Agent Neural Network for Learning Cellular Interaction Dynamics. MLCB João F. Rocha, Ke Xu, Xingzhi Sun, Ananya Krishna, Dhananjay Bhaskar, Blanche Mongeon, Morgan Craig, Mark Gerstein, Smita Krishnaswamy
2025	J	`jnl`	STAGED: A Multi-Agent Neural Network for Learning Cellular Interaction Dynamics. CoRR João F. Rocha, Ke Xu, Xingzhi Sun, Ananya Krishna, Dhananjay Bhaskar, Blanche Mongeon, Morgan Craig, Mark Gerstein, Smita Krishnaswamy
2025	J	`jnl`	Self-Supervised Visual Prompting for Cross-Domain Road Damage Detection. CoRR Xi Xiao, Zhuxuanzi Wang, Mingqiao Mo, Chen Liu, Chenrui Ma, Yanshu Li, Smita Krishnaswamy, Xiao Wang, Tianyang Wang
2025	J	`jnl`	SlepNet: Spectral Subgraph Representation Learning for Neural Dynamics. CoRR Siddharth Viswanath, Rahul Singh, Yanlei Zhang, J. Adam Noah, Joy Hirsch, Smita Krishnaswamy
2024	Misc	`conf`	Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy. CISS Danqi Liao, Chen Liu, Benjamin W. Christensen, Alexander Tong, Guillaume Huguet, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy
2024	A	`conf`	BLIS-Net: Classifying and Analyzing Signals on Graphs. AISTATS Charles Xu, Laney Goldman, Valentina Guo, Benjamin Hollander-Bodie, Maedee Trank-Greene, Ian Adelstein, Edward De Brouwer, Rex Ying, Smita Krishnaswamy, Michael Perlmutter
2024	Misc	`conf`	Bayesian Spectral Graph Denoising with Smoothness Prior. CISS Samuel Leone, Xingzhi Sun, Michael Perlmutter, Smita Krishnaswamy
2024	—	`conf`	CUTS: A Deep Learning and Topological Framework for Multigranular Unsupervised Medical Image Segmentation. MICCAI (8) Chen Liu, Matthew Amodio, Liangbo L. Shen, Feng Gao, Arman Avesta, Sanjay Aneja, Jay C. Wang, Luciano V. Del Priore, Smita Krishnaswamy
2024	J	`jnl`	Convergence of Manifold Filter-Combine Networks. CoRR David R. Johnson, Joyce A. Chew, Siddharth Viswanath, Edward De Brouwer, Deanna Needell, Smita Krishnaswamy, Michael Perlmutter
2024	J	`jnl`	DiffKillR: Killing and Recreating Diffeomorphisms for Cell Annotation in Dense Microscopy Images. CoRR Chen Liu, Danqi Liao, Alejandro Parada-Mayorga, Alejandro Ribeiro, Marcello DiStasio, Smita Krishnaswamy
2024	Misc	`conf`	Directed Scattering for Knowledge Graph-Based Cellular Signaling Analysis. ICASSP Aarthi Venkat, Joyce A. Chew, Ferran Cardoso Rodriguez, Christopher J. Tape, Michael Perlmutter, Smita Krishnaswamy
2024	J	`jnl`	Exploring the Manifold of Neural Networks Using Diffusion Geometry. CoRR Elliott Abel, Peyton Crevasse, Yvan Grinspan, Selma Mazioud, Folu Ogundipe, Kristof Reimann, Ellie Schueler, Andrew J. Steindl, Ellen Zhang, Dhananjay Bhaskar, Siddharth Viswanath, Yanlei Zhang, Tim G. J. Rudner, Ian Adelstein, Smita Krishnaswamy
2024	J	`jnl`	Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds. CoRR Xingzhi Sun, Danqi Liao, Kincaid MacDonald, Yanlei Zhang, Chen Liu, Guillaume Huguet, Guy Wolf, Ian Adelstein, Tim G. J. Rudner, Smita Krishnaswamy
2024	J	`jnl`	Hyperedge Representations with Hypergraph Wavelets: Applications to Spatial Transcriptomics. CoRR Xingzhi Sun, Charles Xu, João F. Rocha, Chen Liu, Benjamin Hollander-Bodie, Laney Goldman, Marcello DiStasio, Michael Perlmutter, Smita Krishnaswamy
2024	J	`jnl`	ImageFlowNet: Forecasting Multiscale Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images. CoRR Chen Liu, Ke Xu, Liangbo L. Shen, Guillaume Huguet, Zilong Wang, Alexander Tong, Danilo Bzdok, Jay Stewart, Jay C. Wang, Luciano V. Del Priore, Smita Krishnaswamy
2024	B	`conf`	Inferring Metabolic States from Single Cell Transcriptomic Data via Geometric Deep Learning. RECOMB Holly R. Steach, Siddharth Viswanath, Yixuan He, Xitong Zhang, Natalia Ivanova, Matthew J. Hirn, Michael Perlmutter, Smita Krishnaswamy
2024	J	`jnl`	Latent Representation Learning for Multimodal Brain Activity Translation. CoRR Arman Afrasiyabi, Dhananjay Bhaskar, Erica L. Busch, Laurent Caplette, Rahul Singh, Guillaume Lajoie, Nicholas B. Turk-Browne, Smita Krishnaswamy
2024	J	`jnl`	Learnable Filters for Geometric Scattering Modules. IEEE Trans. Signal Process. Alexander Tong, Frederik Wenkel, Dhananjay Bhaskar, Kincaid MacDonald, Jackson D. Grady, Michael Perlmutter, Smita Krishnaswamy, Guy Wolf
2024	—	`ed.`	Learning on Graphs Conference, 26-29 November 2024, Virtual. LoG Guy Wolf, Smita Krishnaswamy
2024	J	`jnl`	Looking through the mind's eye via multimodal encoder-decoder networks. CoRR Arman Afrasiyabi, Erica L. Busch, Rahul Singh, Dhananjay Bhaskar, Laurent Caplette, Nicholas B. Turk-Browne, Smita Krishnaswamy
2024	J	`jnl`	Low-Dimensional Embeddings of High-Dimensional Data: Algorithms and Applications (Dagstuhl Seminar 24122). Dagstuhl Reports Dmitry Kobak, Fred A. Hamprecht, Smita Krishnaswamy, Gal Mishne, Sebastian Damrich
2024	J	`jnl`	Mapping the gene space at single-cell resolution with gene signal pattern analysis. Nat. Comput. Sci. Aarthi Venkat, Samuel Leone, Scott E. Youlten, Eric Fagerberg, John Attanasio, Nikhil S. Joshi, Michael Perlmutter, Smita Krishnaswamy
2024	J	`jnl`	ProtSCAPE: Mapping the landscape of protein conformations in molecular dynamics. CoRR Siddharth Viswanath, Dhananjay Bhaskar, David R. Johnson, João F. Rocha, Egbert Castro, Jackson D. Grady, Alex T. Grigas, Michael A. Perlmutter, Corey S. O'Hern, Smita Krishnaswamy
2024	J	`jnl`	StrokeClassifier: ischemic stroke etiology classification by ensemble consensus modeling using electronic health records. npj Digit. Medicine Ho-Joon Lee, Lee H. Schwamm, Lauren H. Sansing, Hooman Kamel, Adam DeHavenon, Ashby C. Turner, Kevin N. Sheth, Smita Krishnaswamy, Cynthia Brandt, Hongyu Zhao, Harlan M. Krumholz, Richa Sharma
2023	—	`conf`	A Flow Artist for High-Dimensional Cellular Data. MLSP Kincaid MacDonald, Dhananjay Bhaskar, Guy Thampakkul, Nhi Nguyen, Joia Zhang, Michael Perlmutter, Ian Adelstein, Smita Krishnaswamy
2023	J	`jnl`	A Flow Artist for High-Dimensional Cellular Data. CoRR Kincaid MacDonald, Dhananjay Bhaskar, Guy Thampakkul, Nhi Nguyen, Joia Zhang, Michael Perlmutter, Ian Adelstein, Smita Krishnaswamy
2023	A*	`conf`	A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction. NeurIPS Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy
2023	J	`jnl`	A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction. CoRR Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy
2023	J	`jnl`	Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy. CoRR Danqi Liao, Chen Liu, Benjamin W. Christensen, Alexander Tong, Guillaume Huguet, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy
2023	J	`jnl`	BLIS-Net: Classifying and Analyzing Signals on Graphs. CoRR Charles Xu, Laney Goldman, Valentina Guo, Benjamin Hollander-Bodie, Maedee Trank-Greene, Ian Adelstein, Edward De Brouwer, Rex Ying, Smita Krishnaswamy, Michael Perlmutter
2023	J	`jnl`	Bayesian Formulations for Graph Spectral Denoising. CoRR Samuel Leone, Xingzhi Sun, Michael Perlmutter, Smita Krishnaswamy
2023	J	`jnl`	Directed Scattering for Knowledge Graph-based Cellular Signaling Analysis. CoRR Aarthi Venkat, Joyce A. Chew, Ferran Cardoso Rodriguez, Christopher J. Tape, Michael Perlmutter, Smita Krishnaswamy
2023	—	`conf`	Geodesic Sinkhorn For Fast and Accurate Optimal Transport on Manifolds. MLSP Guillaume Huguet, Alexander Tong, María Ramos Zapatero, Christopher J. Tape, Guy Wolf, Smita Krishnaswamy
2023	J	`jnl`	Graph Fourier MMD for Signals on Graphs. CoRR Samuel Leone, Aarthi Venkat, Guillaume Huguet, Alexander Tong, Guy Wolf, Smita Krishnaswamy
2023	J	`jnl`	Graph topological property recovery with heat and wave dynamics-based features on graphs. CoRR Dhananjay Bhaskar, Yanlei Zhang, Charles Xu, Xingzhi Sun, Oluwadamilola Fasina, Guy Wolf, Maximilian Nickel, Michael Perlmutter, Smita Krishnaswamy
2023	—	`conf`	Inferring Dynamic Regulatory Interaction Graphs From Time Series Data With Perturbations. LoG Dhananjay Bhaskar, Daniel Sumner Magruder, Matheo Morales, Edward De Brouwer, Aarthi Venkat, Frederik Wenkel, Guy Wolf, Smita Krishnaswamy
2023	J	`jnl`	Inferring dynamic regulatory interaction graphs from time series data with perturbations. CoRR Dhananjay Bhaskar, Daniel Sumner Magruder, Edward De Brouwer, Aarthi Venkat, Frederik Wenkel, Guy Wolf, Smita Krishnaswamy
2023	J	`jnl`	Manifold Filter-Combine Networks. CoRR Joyce A. Chew, Edward De Brouwer, Smita Krishnaswamy, Deanna Needell, Michael Perlmutter
2023	J	`jnl`	Multi-view manifold learning of human brain-state trajectories. Nat. Comput. Sci. Erica L. Busch, Jessie Huang, Andrew Benz, Tom Wallenstein, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy, Nicholas B. Turk-Browne
2023	J	`jnl`	Neural FIM for learning Fisher Information Metrics from point cloud data. CoRR Oluwadamilola Fasina, Guillaume Huguet, Alexander Tong, Yanlei Zhang, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy
2023	A*	`conf`	Neural FIM for learning Fisher information metrics from point cloud data. ICML Oluwadamilola Fasina, Guillaume Huguet, Alexander Tong, Yanlei Zhang, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy
2023	J	`jnl`	Time-Inhomogeneous Diffusion Geometry and Topology. SIAM J. Math. Data Sci. Guillaume Huguet, Alexander Tong, Bastian Rieck, Jessie Huang, Manik Kuchroo, Matthew J. Hirn, Guy Wolf, Smita Krishnaswamy
2023	Misc	`conf`	Wire Before You Walk. ACSSC Tesfa Asmara, Dhananjay Bhaskar, Ian Adelstein, Smita Krishnaswamy, Michael Perlmutter
2022	J	`jnl`	CUTS: A Fully Unsupervised Framework for Medical Image Segmentation. CoRR Matthew Amodio, Feng Gao, Arman Avesta, Sanjay Aneja, Luciano V. Del Priore, Jay Wang, Smita Krishnaswamy
2022	A*	`conf`	Diffusion Curvature for Estimating Local Curvature in High Dimensional Data. NeurIPS Dhananjay Bhaskar, Kincaid MacDonald, Oluwadamilola Fasina, Dawson Thomas, Bastian Rieck, Ian Adelstein, Smita Krishnaswamy
2022	J	`jnl`	Diffusion Curvature for Estimating Local Curvature in High Dimensional Data. CoRR Dhananjay Bhaskar, Kincaid MacDonald, Oluwadamilola Fasina, Dawson Thomas, Bastian Rieck, Ian Adelstein, Smita Krishnaswamy
2022	Misc	`conf`	Embedding Signals on Graphs with Unbalanced Diffusion Earth Mover's Distance. ICASSP Alexander Tong, Guillaume Huguet, Dennis L. Shung, Amine Natik, Manik Kuchroo, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy
2022	B	`conf`	Exploring the Geometry and Topology of Neural Network Loss Landscapes. IDA Stefan Horoi, Jessie Huang, Bastian Rieck, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy
2022	J	`jnl`	Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators. J. Signal Process. Syst. Alexander Tong, Guy Wolf, Smita Krishnaswamy
2022	J	`jnl`	Geodesic Sinkhorn: optimal transport for high-dimensional datasets. CoRR Guillaume Huguet, Alexander Tong, María Ramos Zapatero, Guy Wolf, Smita Krishnaswamy
2022	J	`jnl`	Geometric Scattering on Measure Spaces. CoRR Joyce A. Chew, Matthew J. Hirn, Smita Krishnaswamy, Deanna Needell, Michael Perlmutter, Holly R. Steach, Siddharth Viswanath, Hau-Tieng Wu
2022	J	`jnl`	Guided Generative Protein Design using Regularized Transformers. CoRR Egbert Castro, Abhinav Godavarthi, Julian A. Rubinfien, Kevin B. Givechian, Dhananjay Bhaskar, Smita Krishnaswamy
2022	J	`jnl`	Learnable Filters for Geometric Scattering Modules. CoRR Alexander Tong, Frederik Wenkel, Dhananjay Bhaskar, Kincaid MacDonald, Jackson D. Grady, Michael Perlmutter, Smita Krishnaswamy, Guy Wolf
2022	—	`conf`	Learning Shared Neural Manifolds from Multi-Subject FMRI Data. MLSP Jessie Huang, Erica L. Busch, Tom Wallenstein, Michal Gerasimiuk, Andrew Benz, Guillaume Lajoie, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy
2022	J	`jnl`	Learning shared neural manifolds from multi-subject FMRI data. CoRR Jessie Huang, Erica L. Busch, Tom Wallenstein, Michal Gerasimiuk, Andrew Benz, Guillaume Lajoie, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy
2022	A*	`conf`	Manifold Interpolating Optimal-Transport Flows for Trajectory Inference. NeurIPS Guillaume Huguet, Daniel Sumner Magruder, Alexander Tong, Oluwadamilola Fasina, Manik Kuchroo, Guy Wolf, Smita Krishnaswamy
2022	J	`jnl`	Manifold Interpolating Optimal-Transport Flows for Trajectory Inference. CoRR Guillaume Huguet, Daniel Sumner Magruder, Oluwadamilola Fasina, Alexander Tong, Manik Kuchroo, Guy Wolf, Smita Krishnaswamy
2022	—	`conf`	Molecular Graph Generation via Geometric Scattering. MLSP Dhananjay Bhaskar, Jackson D. Grady, Egbert Castro, Michael Perlmutter, Smita Krishnaswamy
2022	J	`jnl`	Single-cell multi-modal GAN reveals spatial patterns in single-cell data from triple-negative breast cancer. Patterns Matthew Amodio, Scott E. Youlten, Aarthi Venkat, Beatriz P. San Juan, Christine L. Chaffer, Smita Krishnaswamy
2022	—	`conf`	The Manifold Scattering Transform for High-Dimensional Point Cloud Data. TAG-ML Joyce A. Chew, Holly R. Steach, Siddharth Viswanath, Hau-Tieng Wu, Matthew J. Hirn, Deanna Needell, Matthew D. Vesely, Smita Krishnaswamy, Michael Perlmutter
2022	J	`jnl`	The Manifold Scattering Transform for High-Dimensional Point Cloud Data. CoRR Joyce A. Chew, Holly R. Steach, Siddharth Viswanath, Hau-Tieng Wu, Matthew J. Hirn, Deanna Needell, Smita Krishnaswamy, Michael Perlmutter
2022	J	`jnl`	Time-inhomogeneous diffusion geometry and topology. CoRR Guillaume Huguet, Alexander Tong, Bastian Rieck, Jessie Huang, Manik Kuchroo, Matthew J. Hirn, Guy Wolf, Smita Krishnaswamy
2022	J	`jnl`	Transformer-based protein generation with regularized latent space optimization. Nat. Mac. Intell. Egbert Castro, Abhinav Godavarthi, Julian A. Rubinfien, Kevin B. Givechian, Dhananjay Bhaskar, Smita Krishnaswamy
2021	—	`conf`	A sandbox for prediction and integration of DNA, RNA, and proteins in single cells. NeurIPS Datasets and Benchmarks Malte Lücken, Daniel Burkhardt, Robrecht Cannoodt, Christopher Lance, Aditi Agrawal, Hananeh Aliee, Ann Chen, Louise Deconinck, Angela Detweiler, Alejandro Granados, Shelly Huynh, Laura Isacco, Yang Kim, Dominik Klein, Bony de Kumar, Sunil Kuppasani, Heiko Lickert, Aaron McGeever, Joaquin Melgarejo, Honey Mekonen, Maurizio Morri, Michaela Müller, Norma Neff, Sheryl Paul, Bastian Rieck, Kaylie Schneider, Scott Steelman, Michael Sterr, Daniel Treacy, Alexander Tong, Alexandra-Chloé Villani, Guilin Wang, Jia Yan, Ce Zhang, Angela Pisco, Smita Krishnaswamy, Fabian J. Theis, Jonathan M. Bloom
2021	B	`conf`	Canvas GAN: Bootstrapped Image-Conditional Models. IJCNN Matthew Amodio, Smita Krishnaswamy
2021	—	`conf`	Data-Driven Learning of Geometric Scattering Modules for GNNs. MLSP Alexander Tong, Frederick Wenkel, Kincaid MacDonald, Smita Krishnaswamy, Guy Wolf
2021	A*	`conf`	Diffusion Earth Mover's Distance and Distribution Embeddings. ICML Alexander Tong, Guillaume Huguet, Amine Natik, Kincaid MacDonald, Manik Kuchroo, Ronald R. Coifman, Guy Wolf, Smita Krishnaswamy
2021	J	`jnl`	Diffusion Earth Mover's Distance and Distribution Embeddings. CoRR Alexander Tong, Guillaume Huguet, Amine Natik, Kincaid MacDonald, Manik Kuchroo, Ronald R. Coifman, Guy Wolf, Smita Krishnaswamy
2021	J	`jnl`	Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance. CoRR Alexander Tong, Guillaume Huguet, Dennis L. Shung, Amine Natik, Manik Kuchroo, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy
2021	J	`jnl`	Generating hard-to-obtain information from easy-to-obtain information: Applications in drug discovery and clinical inference. Patterns Matthew Amodio, Dennis L. Shung, Daniel B. Burkhardt, Patrick Wong, Michael Simonov, Yu Yamamoto, David van Dijk, Francis Perry Wilson, Akiko Iwasaki, Smita Krishnaswamy
2021	—	`conf`	MURAL: An Unsupervised Random Forest-Based Embedding for Electronic Health Record Data. IEEE BigData Michal Gerasimiuk, Dennis L. Shung, Alexander Tong, Adrian J. Stanley, Michael Schultz, Jeffrey Ngu, Loren Laine, Guy Wolf, Smita Krishnaswamy
2021	J	`jnl`	MURAL: An Unsupervised Random Forest-Based Embedding for Electronic Health Record Data. CoRR Michal Gerasimiuk, Dennis L. Shung, Alexander Tong, Adrian J. Stanley, Michael Schultz, Jeffrey Ngu, Loren Laine, Guy Wolf, Smita Krishnaswamy
2021	J	`jnl`	Molecular Graph Generation via Geometric Scattering. CoRR Dhananjay Bhaskar, Jackson D. Grady, Michael A. Perlmutter, Smita Krishnaswamy
2021	—	`conf`	Multimodal Data Visualization and Denoising with Integrated Diffusion. MLSP Manik Kuchroo, Abhinav Godavarthi, Alexander Tong, Guy Wolf, Smita Krishnaswamy
2021	J	`jnl`	Multimodal data visualization, denoising and clustering with integrated diffusion. CoRR Manik Kuchroo, Abhinav Godavarthi, Guy Wolf, Smita Krishnaswamy
2021	—	`conf`	Multimodal single cell data integration challenge: Results and lessons learned. NeurIPS (Competition and Demos) Christopher Lance, Malte D. Lücken, Daniel B. Burkhardt, Robrecht Cannoodt, Pia Rautenstrauch, Anna Laddach, Aidyn Ubingazhibov, Zhi-Jie Cao, Kaiwen Deng, Sumeer Khan, Qiao Liu, Nikolay Russkikh, Gleb Ryazantsev, Uwe Ohler, Angela Oliveira Pisco, Jonathan Bloom, Smita Krishnaswamy, Fabian J. Theis
2021	B	`conf`	Multiple-manifold Generation with an Ensemble GAN and Learned Noise Prior. IDA Matthew Amodio, Smita Krishnaswamy
2021	B	`conf`	Noise Space Optimization for GANs. IJCNN Matthew Amodio, Smita Krishnaswamy
2021	J	`jnl`	Visualizing High-Dimensional Trajectories on the Loss-Landscape of ANNs. CoRR Stefan Horoi, Jessie Huang, Guy Wolf, Smita Krishnaswamy
2020	J	`jnl`	Data-Driven Learning of Geometric Scattering Networks. CoRR Alexander Tong, Frederik Wenkel, Kincaid MacDonald, Smita Krishnaswamy, Guy Wolf
2020	—	`conf`	Fixing Bias in Reconstruction-Based Anomaly Detection with Lipschitz Discriminators. MLSP Alexander Tong, Guy Wolf, Smita Krishnaswamy
2020	A	`conf`	Harmonic Alignment. SDM Jay S. Stanley III, Scott Gigante, Guy Wolf, Smita Krishnaswamy
2020	J	`jnl`	Image-to-image Mapping with Many Domains by Sparse Attribute Transfer. CoRR Matthew Amodio, Rim Assouel, Victor Schmidt, Tristan Sylvain, Smita Krishnaswamy, Yoshua Bengio
2020	B	`conf`	Interpretable Neuron Structuring with Graph Spectral Regularization. IDA Alexander Tong, David van Dijk, Jay S. Stanley III, Matthew Amodio, Kristina Yim, Rebecca Muhle, James Noonan, Guy Wolf, Smita Krishnaswamy
2020	—	`conf`	Learning General Transformations of Data for Out-of-Sample Extensions. MLSP Matthew Amodio, David van Dijk, Guy Wolf, Smita Krishnaswamy
2020	J	`jnl`	Making Logic Learnable With Neural Networks. CoRR Tobias Brudermueller, Dennis L. Shung, Loren Laine, Adrian J. Stanley, Stig B. Laursen, Harry R. Dalton, Jeffrey Ngu, Michael Schultz, Johannes Stegmaier, Smita Krishnaswamy
2020	A*	`conf`	TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. ICML Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy
2020	J	`jnl`	TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. CoRR Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy
2020	—	`conf`	Uncovering the Folding Landscape of RNA Secondary Structure Using Deep Graph Embeddings. IEEE BigData Egbert Castro, Andrew Benz, Alexander Tong, Guy Wolf, Smita Krishnaswamy
2020	J	`jnl`	Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings. CoRR Egbert Castro, Andrew Benz, Alexander Tong, Guy Wolf, Smita Krishnaswamy
2020	A*	`conf`	Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence. NeurIPS Bastian Rieck, Tristan Yates, Christian Bock, Karsten M. Borgwardt, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy
2020	J	`jnl`	Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence. CoRR Bastian Rieck, Tristan Yates, Christian Bock, Karsten M. Borgwardt, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy
2019	J	`jnl`	A Lipschitz-constrained anomaly discriminator framework. CoRR Alexander Tong, Guy Wolf, Smita Krishnaswamy
2019	—	`conf`	Coarse Graining of Data via Inhomogeneous Diffusion Condensation. IEEE BigData 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
2019	J	`jnl`	Coarse Graining of Data via Inhomogeneous Diffusion Condensation. CoRR 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
2019	J	`jnl`	Compressed Diffusion. CoRR Scott Gigante, Jay S. Stanley III, Ngan Vu, David van Dijk, Kevin R. Moon, Guy Wolf, Smita Krishnaswamy
2019	—	`conf`	Finding Archetypal Spaces Using Neural Networks. IEEE BigData David van Dijk, Daniel B. Burkhardt, Matthew Amodio, Alexander Tong, Guy Wolf, Smita Krishnaswamy
2019	J	`jnl`	Finding Archetypal Spaces for Data Using Neural Networks. CoRR David van Dijk, Daniel B. Burkhardt, Matthew Amodio, Alexander Tong, Guy Wolf, Smita Krishnaswamy
2019	J	`jnl`	Generating and Aligning from Data Geometries with Generative Adversarial Networks. CoRR Matthew Amodio, Smita Krishnaswamy
2019	A*	`conf`	TraVeLGAN: Image-To-Image Translation by Transformation Vector Learning. CVPR Matthew Amodio, Smita Krishnaswamy
2019	J	`jnl`	TraVeLGAN: Image-to-image Translation by Transformation Vector Learning. CoRR Matthew Amodio, Smita Krishnaswamy
2019	—	`conf`	Vertex-Frequency Clustering. DSW Daniel B. Burkhardt, Jay S. Stanley III, Guy Wolf, Smita Krishnaswamy
2019	A*	`conf`	Visualizing the PHATE of Neural Networks. NeurIPS Scott Gigante, Adam S. Charles, Smita Krishnaswamy, Gal Mishne
2019	J	`jnl`	Visualizing the PHATE of Neural Networks. CoRR Scott Gigante, Adam S. Charles, Smita Krishnaswamy, Gal Mishne
2018	A*	`conf`	Geometry Based Data Generation. NeurIPS Ofir Lindenbaum, Jay S. Stanley III, Guy Wolf, Smita Krishnaswamy
2018	J	`jnl`	Geometry-Based Data Generation. CoRR Ofir Lindenbaum, Jay S. Stanley III, Guy Wolf, Smita Krishnaswamy
2018	J	`jnl`	Graph Spectral Regularization for Neural Network Interpretability. CoRR Alexander Tong, David van Dijk, Jay S. Stanley III, Matthew Amodio, Guy Wolf, Smita Krishnaswamy
2018	A*	`conf`	MAGAN: Aligning Biological Manifolds. ICML Matthew Amodio, Smita Krishnaswamy
2018	J	`jnl`	MAGAN: Aligning Biological Manifolds. CoRR Matthew Amodio, Smita Krishnaswamy
2018	J	`jnl`	Manifold Alignment with Feature Correspondence. CoRR Jay S. Stanley III, Guy Wolf, Smita Krishnaswamy
2018	J	`jnl`	Modeling Dynamics with Deep Transition-Learning Networks. CoRR David van Dijk, Scott Gigante, Alexander Strzalkowski, Guy Wolf, Smita Krishnaswamy
2013	A*	`conf`	Can CAD cure cancer? DAC Smita Krishnaswamy, Bernd Bodenmiller, Dana Pe'er
2013	—	`book`	Design, Analysis and Test of Logic Circuits Under Uncertainty Smita Krishnaswamy, Igor L. Markov, John P. Hayes
2013	A	`conf`	Intuitive ECO synthesis for high performance circuits. DATE Haoxing Ren, Ruchir Puri, Lakshmi N. Reddy, Smita Krishnaswamy, Cindy Washburn, Joel Earl, Joachim Keinert
2012	A*	`conf`	Generalized SAT-sweeping for post-mapping optimization. DAC Tobias Welp, Smita Krishnaswamy, Andreas Kuehlmann
2011	A*	`conf`	Joint DAC/IWBDA special session design and synthesis of biological circuits. DAC Douglas Densmore, Mark Horowitz, Smita Krishnaswamy, Xiling Shen, Adam P. Arkin, Erik Winfree, Chris Voigt
2010	A	`conf`	SPIRE: A retiming-based physical-synthesis transformation system. ICCAD David A. Papa, Smita Krishnaswamy, Igor L. Markov
2009	A	`conf`	DeltaSyn: An efficient logic difference optimizer for ECO synthesis. ICCAD Smita Krishnaswamy, Haoxing Ren, Nilesh Modi, Ruchir Puri
2009	A*	`conf`	Improving testability and soft-error resilience through retiming. DAC Smita Krishnaswamy, Igor L. Markov, John P. Hayes
2009	J	`jnl`	Signature-Based SER Analysis and Design of Logic Circuits. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Smita Krishnaswamy, Stephen Plaza, Igor L. Markov, John P. Hayes
2008	—	`—`	Design, Analysis and Test of Logic Circuits under Uncertainty. Smita Krishnaswamy
2008	A*	`conf`	On the role of timing masking in reliable logic circuit design. DAC Smita Krishnaswamy, Igor L. Markov, John P. Hayes
2008	J	`jnl`	Probabilistic transfer matrices in symbolic reliability analysis of logic circuits. ACM Trans. Design Autom. Electr. Syst. Smita Krishnaswamy, George F. Viamontes, Igor L. Markov, John P. Hayes
2007	A	`conf`	Enhancing design robustness with reliability-aware resynthesis and logic simulation. ICCAD Smita Krishnaswamy, Stephen Plaza, Igor L. Markov, John P. Hayes
2007	J	`jnl`	Tracking Uncertainty with Probabilistic Logic Circuit Testing. IEEE Des. Test Comput. Smita Krishnaswamy, Igor L. Markov, John P. Hayes
2005	A	`conf`	Accurate Reliability Evaluation and Enhancement via Probabilistic Transfer Matrices. DATE Smita Krishnaswamy, George F. Viamontes, Igor L. Markov, John P. Hayes
2005	B	`conf`	Logic circuit testing for transient faults. ETS Smita Krishnaswamy, Igor L. Markov, John P. Hayes