Henry Kvinge

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 62

Top Topics

Internal Representations

Dimensionality Reduction

Top Venues

Publications

Davis Brown, Cody Nizinski, Madelyn Shapiro, Corey Fallon, Tianzhixi Yin, Henry Kvinge, Jonathan H. Tu
Model editing for distribution shifts in uranium oxide morphological analysis. CoRR (2024)
Sai Munikoti, Ian Stewart, Sameera Horawalavithana, Henry Kvinge, Tegan Emerson, Sandra E. Thompson, Karl Pazdernik
Generalist Multimodal AI: A Review of Architectures, Challenges and Opportunities. CoRR (2024)
Nicholas Konz, Charles Godfrey, Madelyn Shapiro, Jonathan Tu, Henry Kvinge, Davis Brown
Attributing Learned Concepts in Neural Networks to Training Data. CoRR (2023)
Scott Howland, Lara Kassab, Keerti Kappagantula, Henry Kvinge, Tegan Emerson
Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Towards ML-assisted Advanced Manufacturing. CoRR (2023)
Audun Myers, Henry Kvinge, Tegan Emerson
TopFusion: Using Topological Feature Space for Fusion and Imputation in Multi-Modal Data. CVPR Workshops (2023)
Davis Brown, Charles Godfrey, Nicholas Konz, Jonathan Tu, Henry Kvinge
Understanding the Inner-workings of Language Models Through Representation Dissimilarity. EMNLP (2023)
Mathilde Papillon, Mustafa Hajij, Audun Myers, Florian Frantzen, Ghada Zamzmi, Helen Jenne, Johan Mathe, Josef Hoppe, Michael T. Schaub, Theodore Papamarkou, Aldo Guzmán-Sáenz, Bastian Rieck, Neal Livesay, Tamal K. Dey, Abraham Rabinowitz, Aiden Brent, Alessandro Salatiello, Alexander Nikitin, Ali Zia, Claudio Battiloro, Dmitrii Gavrilev, Georg Bökman, German Magai, Gleb Bazhenov, Guillermo Bernárdez, Indro Spinelli, Jens Agerberg, Kalyan Varma Nadimpalli, Lev Telyatnikov, Luca Scofano, Lucia Testa, Manuel Lecha, Maosheng Yang, Mohammed Hassanin, Odin Hoff Gardaa, Olga Zaghen, Paul Häusner, Paul Snopoff, Pavlo Melnyk, Rubén Ballester, Sadrodin Barikbin, Sergio Escalera, Simone Fiorellino, Henry Kvinge, Jan Meissner, Karthikeyan Natesan Ramamurthy, Michael Scholkemper, Paul Rosen, Robin Walters, Shreyas N. Samaga, Soham Mukherjee, Sophia Sanborn, Tegan Emerson, Timothy Doster, Tolga Birdal, Vincent P. Grande, Abdelwahed Khamis, Simone Scardapane, Suraj Singh, Tatiana Malygina, Yixiao Yue, Nina Miolane
ICML 2023 Topological Deep Learning Challenge: Design and Results. TAG-ML (2023)
Charles Godfrey, Henry Kvinge, Elise Bishoff, Myles Mckay, Davis Brown, Tim Doster, Eleanor Byler
How many dimensions are required to find an adversarial example? CVPR Workshops (2023)
Davis Brown, Charles Godfrey, Nicholas Konz, Jonathan Tu, Henry Kvinge
Understanding the Inner Workings of Language Models Through Representation Dissimilarity. CoRR (2023)
Davis Brown, Charles Godfrey, Cody Nizinski, Jonathan Tu, Henry Kvinge
Robustness of edited neural networks. CoRR (2023)
Cody Tipton, Elizabeth Coda, Davis Brown, Alyson Bittner, Jung H. Lee, Grayson Jorgenson, Tegan Emerson, Henry Kvinge
Haldane Bundles: A Dataset for Learning to Predict the Chern Number of Line Bundles on the Torus. CoRR (2023)
Mathilde Papillon, Mustafa Hajij, Florian Frantzen, Josef Hoppe, Helen Jenne, Johan Mathe, Audun Myers, Theodore Papamarkou, Michael T. Schaub, Ghada Zamzmi, Tolga Birdal, Tamal K. Dey, Tim Doster, Tegan Emerson, Gurusankar Gopalakrishnan, Devendra Govil, Vincent P. Grande, Aldo Guzmán-Sáenz, Henry Kvinge, Neal Livesay, Jan Meisner, Soham Mukherjee, Shreyas N. Samaga, Karthikeyan Natesan Ramamurthy, Maneel Reddy Karri, Paul Rosen, Sophia Sanborn, Michael Scholkemper, Robin Walters, Jens Agerberg, Georg Bökman, Sadrodin Barikbin, Claudio Battiloro, Gleb Bazhenov, Guillermo Bernárdez, Aiden Brent, Sergio Escalera, Simone Fiorellino, Dmitrii Gavrilev, Mohammed Hassanin, Paul Häusner, Odin Hoff Gardaa, Abdelwahed Khamis, Manuel Lecha, German Magai, Tatiana Malygina, Pavlo Melnyk, et al.
ICML 2023 Topological Deep Learning Challenge : Design and Results. CoRR (2023)
Timothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn
Preface. TAG-ML (2023)
Davis Brown, Henry Kvinge
Making Corgis Important for Honeycomb Classification: Adversarial Attacks on Concept-based Explainability Tools. CVPR Workshops (2023)
Henry Kvinge, Davis Brown, Charles Godfrey
Exploring the Representation Manifolds of Stable Diffusion Through the Lens of Intrinsic Dimension. CoRR (2023)
Cuong Ly, Grayson Jorgenson, Dan Rosa de Jesus, Henry Kvinge, Adam Attarian, Yijing Watkins
ColMix - A Simple Data Augmentation Framework to Improve Object Detector Performance and Robustness in Aerial Images. CoRR (2023)
Charles Godfrey, Michael G. Rawson, Davis Brown, Henry Kvinge
Fast computation of permutation equivariant layers with the partition algebra. CoRR (2023)
Sameera Horawalavithana, Sai Munikoti, Ian Stewart, Henry Kvinge
SCITUNE: Aligning Large Language Models with Scientific Multimodal Instructions. CoRR (2023)
Charles Godfrey, Henry Kvinge, Elise Bishoff, Myles Mckay, Davis Brown, Tim Doster, Eleanor Byler
How many dimensions are required to find an adversarial example? CoRR (2023)
Sarah McGuire, Shane Jackson, Tegan Emerson, Henry Kvinge
Do neural networks trained with topological features learn different internal representations? NeurReps (2022)
Henry Kvinge, Tegan Emerson, Grayson Jorgenson, Scott Vasquez, Tim Doster, Jesse D. Lew
In What Ways Are Deep Neural Networks Invariant and How Should We Measure This? NeurIPS (2022)
Alexander Cloninger, Timothy Doster, Tegan Emerson, Manohar Kaul, Ira Ktena, Henry Kvinge, Nina Miolane, Bastian Rice, Sarah Tymochko, Guy Wolf
Preface. TAG-ML (2022)
Charles Godfrey, Davis Brown, Tegan Emerson, Henry Kvinge
On the Symmetries of Deep Learning Models and their Internal Representations. NeurIPS (2022)
Lara Kassab, Scott Howland, Henry Kvinge, Keerti Sahithi Kappagantula, Tegan Emerson
TopTemp: Parsing Precipitate Structure from Temper Topology. CoRR (2022)
Sarah McGuire, Shane Jackson, Tegan Emerson, Henry Kvinge
Do Neural Networks Trained with Topological Features Learn Different Internal Representations? CoRR (2022)
Charles Godfrey, Davis Brown, Tegan Emerson, Henry Kvinge
On the Symmetries of Deep Learning Models and their Internal Representations. CoRR (2022)
Elizabeth Coda, Nico Courts, Colby Wight, Loc Truong, Woongjo Choi, Charles Godfrey, Tegan Emerson, Keerti Kappagantula, Henry Kvinge
Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many Maps. CoRR (2022)
Nico Courts, Henry Kvinge
Bundle Networks: Fiber Bundles, Local Trivializations, and a Generative Approach to Exploring Many-to-one Maps. ICLR (2022)
Charles Godfrey, Elise Bishoff, Myles Mckay, Davis Brown, Grayson Jorgenson, Henry Kvinge, Eleanor Byler
Convolutional networks inherit frequency sensitivity from image statistics. CoRR (2022)
Henry Kvinge, Tegan H. Emerson, Grayson Jorgenson, Scott Vasquez, Timothy Doster, Jesse D. Lew
In What Ways Are Deep Neural Networks Invariant and How Should We Measure This? CoRR (2022)
Lara Kassab, Scott Howland, Henry Kvinge, Keerti Sahithi Kappagantula, Tegan Emerson
TopTemp: Parsing Precipitate Structure from Temper Topology. TAG-ML (2022)
Elizabeth Coda, Nico Courts, Colby Wight, Loc Truong, WoongJo Choi, Charles Godfrey, Tegan Emerson, Keerti Kappagantula, Henry Kvinge
Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many Maps. TAG-ML (2022)
Henry Kvinge, Grayson Jorgenson, Davis Brown, Charles Godfrey, Tegan Emerson
Neural frames: A Tool for Studying the Tangent Bundles Underlying Image Datasets and How Deep Learning Models Process Them. CoRR (2022)
Grayson Jorgenson, Henry Kvinge, Tegan Emerson, Colin C. Olson
Random Filters for Enriching the Discriminatory power of Topological Representations. TAG-ML (2022)
Henry Kvinge, Brett A. Jefferson, Cliff A. Joslyn, Emilie Purvine
Sheaves as a Framework for Understanding and Interpreting Model Fit. ICCVW (2021)
Scott Mahan, Tim Doster, Henry Kvinge
DNA: Dynamic Network Augmentation. CoRR (2021)
Elliott Skomski, Aaron Tuor, Andrew Avila, Lauren A. Phillips, Zachary New, Henry Kvinge, Courtney D. Corley, Nathan O. Hodas
Prototypical Region Proposal Networks for Few-Shot Localization and Classification. CoRR (2021)
Loc Truong, Woongjo Choi, Colby Wight, Lizzy Coda, Tegan Emerson, Keerti Kappagantula, Henry Kvinge
Differential Property Prediction: A Machine Learning Approach to Experimental Design in Advanced Manufacturing. CoRR (2021)
Song Feng, Emily Heath, Brett A. Jefferson, Cliff A. Joslyn, Henry Kvinge, Hugh D. Mitchell, Brenda Praggastis, Amie J. Eisfeld, Amy C. Sims, Larissa B. Thackray, Shufang Fan, Kevin B. Walters, Peter J. Halfmann, Danielle Westhoff-Smith, Qing Tan, Vineet D. Menachery, Timothy P. Sheahan, Adam S. Cockrell, Jacob F. Kocher, Kelly G. Stratton, Natalie C. Heller, Lisa M. Bramer, Michael S. Diamond, Ralph S. Baric, Katrina M. Waters, Yoshihiro Kawaoka, Jason E. McDermott, Emilie Purvine
Hypergraph models of biological networks to identify genes critical to pathogenic viral response. BMC Bioinform. 22 (1) (2021)
Henry Kvinge, Zachary New, Nico Courts, Jung H. Lee, Lauren A. Phillips, Courtney D. Corley, Aaron Tuor, Andrew Avila, Nathan O. Hodas
Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task Generalization in Few-shot Learning. MetaDL@AAAI (2021)
Henry Kvinge, Colby Wight, Sarah Akers, Scott Howland, Woongjo Choi, Xiaolong Ma, Luke Gosink, Elizabeth Jurrus, Keerti Kappagantula, Tegan H. Emerson
A Topological-Framework to Improve Analysis of Machine Learning Model Performance. CoRR (2021)
Scott Mahan, Henry Kvinge, Tim Doster
Rotating spiders and reflecting dogs: a class conditional approach to learning data augmentation distributions. CoRR (2021)
Davis Brown, Henry Kvinge
Brittle interpretations: The Vulnerability of TCAV and Other Concept-based Explainability Tools to Adversarial Attack. CoRR (2021)
Nico Courts, Henry Kvinge
Bundle Networks: Fiber Bundles, Local Trivializations, and a Generative Approach to Exploring Many-to-one Maps. CoRR (2021)
Henry Kvinge, Scott Howland, Nico Courts, Lauren A. Phillips, John Buckheit, Zachary New, Elliott Skomski, Jung H. Lee, Sandeep Tiwari, Jessica Hibler, Courtney D. Corley, Nathan O. Hodas
One Representation to Rule Them All: Identifying Out-of-Support Examples in Few-shot Learning with Generic Representations. CoRR (2021)
Henry Kvinge, Brett A. Jefferson, Cliff A. Joslyn, Emilie Purvine
Sheaves as a Framework for Understanding and Interpreting Model Fit. CoRR (2021)
Mark Blumstein, Henry Kvinge
Multi-Dimensional Scaling on Groups. ICCVW (2021)
Henry Kvinge, Zachary New, Nico Courts, Jung H. Lee, Lauren A. Phillips, Courtney D. Corley, Aaron Tuor, Andrew Avila, Nathan O. Hodas
Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task Generalization in Few-shot Learning. CoRR (2020)
Elin Farnell, Henry Kvinge, John P. Dixon, Julia R. Dupuis, Michael Kirby, Chris Peterson, Elizabeth C. Schundler, Christian W. Smith
A data-driven approach to sampling matrix selection for compressive sensing. CoRR (2019)
Henry Kvinge, Elin Farnell, Julia R. Dupuis, Michael Kirby, Chris Peterson, Elizabeth C. Schundler
More chemical detection through less sampling: amplifying chemical signals in hyperspectral data cubes through compressive sensing. CoRR (2019)
Henry Kvinge, Elin Farnell, Jingya Li, Yujia Chen
Rare Geometries: Revealing Rare Categories via Dimension-Driven Statistics. ICMLA (2019)
Henry Kvinge, Michael Kirby, Chris Peterson, Chad Eitel, Tod Clapp
A Walk Through Spectral Bands: Using Virtual Reality to Better Visualize Hyperspectral Data. WSOM+ (2019)
Henry Kvinge, Elin Farnell
Rare geometries: revealing rare categories via dimension-driven statistics. CoRR (2019)
Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson
Monitoring the shape of weather, soundscapes, and dynamical systems: a new statistic for dimension-driven data analysis on large datasets. IEEE BigData (2018)
Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson
Monitoring the shape of weather, soundscapes, and dynamical systems: a new statistic for dimension-driven data analysis on large data sets. CoRR (2018)
Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson
A GPU-Oriented Algorithm Design for Secant-Based Dimensionality Reduction. CoRR (2018)
Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson
A GPU-Oriented Algorithm Design for Secant-Based Dimensionality Reduction. ISPDC (2018)
Elin Farnell, Henry Kvinge, Michael Kirby, Chris Peterson
Endmember Extraction on the Grassmannian. DSW (2018)
Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson
Too many secants: a hierarchical approach to secant-based dimensionality reduction on large data sets. HPEC (2018)
Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson
Too many secants: a hierarchical approach to secant-based dimensionality reduction on large data sets. CoRR (2018)
Henry Kvinge, Mark Blumstein
Letting symmetry guide visualization: multidimensional scaling on groups. CoRR (2018)
Elin Farnell, Henry Kvinge, Michael Kirby, Chris Peterson
Endmember Extraction on the Grassmannian. CoRR (2018)