Smita Krishnaswamy

Orcid: 0000-0001-5823-1985

Affiliations:
  • Yale University, New Haven, CT, USA
  • University of Michigan, USA (PhD 2008)


According to our database1, Smita Krishnaswamy authored at least 86 papers between 2005 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2024
Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy.
Proceedings of the 58th Annual Conference on Information Sciences and Systems, 2024

Bayesian Spectral Graph Denoising with Smoothness Prior.
Proceedings of the 58th Annual Conference on Information Sciences and Systems, 2024

2023
Time-Inhomogeneous Diffusion Geometry and Topology.
SIAM J. Math. Data Sci., June, 2023

Multi-view manifold learning of human brain-state trajectories.
Nat. Comput. Sci., 2023

Bayesian Formulations for Graph Spectral Denoising.
CoRR, 2023

BLIS-Net: Classifying and Analyzing Signals on Graphs.
CoRR, 2023

Graph topological property recovery with heat and wave dynamics-based features on graphs.
CoRR, 2023

Directed Scattering for Knowledge Graph-based Cellular Signaling Analysis.
CoRR, 2023

Manifold Filter-Combine Networks.
CoRR, 2023

Inferring dynamic regulatory interaction graphs from time series data with perturbations.
CoRR, 2023

Graph Fourier MMD for Signals on Graphs.
CoRR, 2023

A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Flow Artist for High-Dimensional Cellular Data.
Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

Geodesic Sinkhorn For Fast and Accurate Optimal Transport on Manifolds.
Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

Neural FIM for learning Fisher information metrics from point cloud data.
Proceedings of the International Conference on Machine Learning, 2023

Wire Before You Walk.
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

2022
Transformer-based protein generation with regularized latent space optimization.
Nat. Mac. Intell., October, 2022

Fixing Bias in Reconstruction-based Anomaly Detection with Lipschitz Discriminators.
J. Signal Process. Syst., 2022

Single-cell multi-modal GAN reveals spatial patterns in single-cell data from triple-negative breast cancer.
Patterns, 2022

Geodesic Sinkhorn: optimal transport for high-dimensional datasets.
CoRR, 2022

CUTS: A Fully Unsupervised Framework for Medical Image Segmentation.
CoRR, 2022

Geometric Scattering on Measure Spaces.
CoRR, 2022

Learnable Filters for Geometric Scattering Modules.
CoRR, 2022

The Manifold Scattering Transform for High-Dimensional Point Cloud Data.
CoRR, 2022

Guided Generative Protein Design using Regularized Transformers.
CoRR, 2022

The Manifold Scattering Transform for High-Dimensional Point Cloud Data.
Proceedings of the Topological, 2022

Manifold Interpolating Optimal-Transport Flows for Trajectory Inference.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Diffusion Curvature for Estimating Local Curvature in High Dimensional Data.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Shared Neural Manifolds from Multi-Subject FMRI Data.
Proceedings of the 32nd IEEE International Workshop on Machine Learning for Signal Processing, 2022

Molecular Graph Generation via Geometric Scattering.
Proceedings of the 32nd IEEE International Workshop on Machine Learning for Signal Processing, 2022

Exploring the Geometry and Topology of Neural Network Loss Landscapes.
Proceedings of the Advances in Intelligent Data Analysis XX, 2022

Embedding Signals on Graphs with Unbalanced Diffusion Earth Mover's Distance.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
Generating hard-to-obtain information from easy-to-obtain information: Applications in drug discovery and clinical inference.
Patterns, 2021

Molecular Graph Generation via Geometric Scattering.
CoRR, 2021

Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance.
CoRR, 2021

Multimodal data visualization, denoising and clustering with integrated diffusion.
CoRR, 2021

Visualizing High-Dimensional Trajectories on the Loss-Landscape of ANNs.
CoRR, 2021


Multimodal single cell data integration challenge: Results and lessons learned.
Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Data-Driven Learning of Geometric Scattering Modules for GNNs.
Proceedings of the 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), 2021

Multimodal Data Visualization and Denoising with Integrated Diffusion.
Proceedings of the 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), 2021

Canvas GAN: Bootstrapped Image-Conditional Models.
Proceedings of the International Joint Conference on Neural Networks, 2021

Noise Space Optimization for GANs.
Proceedings of the International Joint Conference on Neural Networks, 2021

Multiple-manifold Generation with an Ensemble GAN and Learned Noise Prior.
Proceedings of the Advances in Intelligent Data Analysis XIX, 2021

Diffusion Earth Mover's Distance and Distribution Embeddings.
Proceedings of the 38th International Conference on Machine Learning, 2021

MURAL: An Unsupervised Random Forest-Based Embedding for Electronic Health Record Data.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020
Data-Driven Learning of Geometric Scattering Networks.
CoRR, 2020

Image-to-image Mapping with Many Domains by Sparse Attribute Transfer.
CoRR, 2020

Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings.
CoRR, 2020

Making Logic Learnable With Neural Networks.
CoRR, 2020

Harmonic Alignment.
Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning General Transformations of Data for Out-of-Sample Extensions.
Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

Interpretable Neuron Structuring with Graph Spectral Regularization.
Proceedings of the Advances in Intelligent Data Analysis XVIII, 2020

TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics.
Proceedings of the 37th International Conference on Machine Learning, 2020

Uncovering the Folding Landscape of RNA Secondary Structure Using Deep Graph Embeddings.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019
A Lipschitz-constrained anomaly discriminator framework.
CoRR, 2019

Compressed Diffusion.
CoRR, 2019

Finding Archetypal Spaces for Data Using Neural Networks.
CoRR, 2019

Generating and Aligning from Data Geometries with Generative Adversarial Networks.
CoRR, 2019

Visualizing the PHATE of Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Vertex-Frequency Clustering.
Proceedings of the IEEE Data Science Workshop, 2019

TraVeLGAN: Image-To-Image Translation by Transformation Vector Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Finding Archetypal Spaces Using Neural Networks.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Coarse Graining of Data via Inhomogeneous Diffusion Condensation.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018
Graph Spectral Regularization for Neural Network Interpretability.
CoRR, 2018

Manifold Alignment with Feature Correspondence.
CoRR, 2018

Modeling Dynamics with Deep Transition-Learning Networks.
CoRR, 2018

Geometry Based Data Generation.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

MAGAN: Aligning Biological Manifolds.
Proceedings of the 35th International Conference on Machine Learning, 2018

2013
Design, Analysis and Test of Logic Circuits Under Uncertainty
Lecture Notes in Electrical Engineering 115, Springer, ISBN: 978-90-481-9643-2, 2013

Intuitive ECO synthesis for high performance circuits.
Proceedings of the Design, Automation and Test in Europe, 2013

Can CAD cure cancer?
Proceedings of the 50th Annual Design Automation Conference 2013, 2013

2012
Generalized SAT-sweeping for post-mapping optimization.
Proceedings of the 49th Annual Design Automation Conference 2012, 2012

2011
Joint DAC/IWBDA special session design and synthesis of biological circuits.
Proceedings of the 48th Design Automation Conference, 2011

2010
SPIRE: A retiming-based physical-synthesis transformation system.
Proceedings of the 2010 International Conference on Computer-Aided Design, 2010

2009
Signature-Based SER Analysis and Design of Logic Circuits.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2009

DeltaSyn: An efficient logic difference optimizer for ECO synthesis.
Proceedings of the 2009 International Conference on Computer-Aided Design, 2009

Improving testability and soft-error resilience through retiming.
Proceedings of the 46th Design Automation Conference, 2009

2008
Design, Analysis and Test of Logic Circuits under Uncertainty.
PhD thesis, 2008

Probabilistic transfer matrices in symbolic reliability analysis of logic circuits.
ACM Trans. Design Autom. Electr. Syst., 2008

On the role of timing masking in reliable logic circuit design.
Proceedings of the 45th Design Automation Conference, 2008

2007
Tracking Uncertainty with Probabilistic Logic Circuit Testing.
IEEE Des. Test Comput., 2007

Enhancing design robustness with reliability-aware resynthesis and logic simulation.
Proceedings of the 2007 International Conference on Computer-Aided Design, 2007

2005
Logic circuit testing for transient faults.
Proceedings of the 10th European Test Symposium, 2005

Accurate Reliability Evaluation and Enhancement via Probabilistic Transfer Matrices.
Proceedings of the 2005 Design, 2005


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