Kristofer E. Bouchard

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 41

Top Topics

Nonnegative Matrix

Linear Dynamical Systems

Top Venues

Frontiers Neuroinformatics

PLoS Comput. Biol.

Publications

Matthew Avaylon, Ryan Ly, Andrew J. Tritt, Benjamin K. Dichter, Kristofer E. Bouchard, Christopher J. Mungall, Oliver Rübel
Methods for Linking Data to Online Resources and Ontologies with Applications to Neurophysiology. CoRR (2024)
Ankit Kumar, Sharmodeep Bhattacharyya, Kristofer E. Bouchard
Numerical characterization of support recovery in sparse regression with correlated design. Commun. Stat. Simul. Comput. 53 (3) (2024)
Marcin P. Joachimiak, Mark A. Miller, J. Harry Caufield, Ryan Ly, Nomi L. Harris, Andrew J. Tritt, Christopher J. Mungall, Kristofer E. Bouchard
The Artificial Intelligence Ontology: LLM-assisted construction of AI concept hierarchies. CoRR (2024)
Zhe Bai, Abdelilah Essiari, Talita Perciano, Kristofer E. Bouchard
AutoCT: Automated CT registration, segmentation, and quantification. SoftwareX 26 (2024)
Zhe Bai, Abdelilah Essiari, Talita Perciano, Kristofer E. Bouchard
AutoCT: Automated CT registration, segmentation, and quantification. CoRR (2023)
E. A. Huerta, Ben Blaiszik, L. Catherine Brinson, Kristofer E. Bouchard, Daniel Diaz, Caterina Doglioni, Javier M. Duarte, Murali Emani, Ian T. Foster, Geoffrey C. Fox, Philip C. Harris, Lukas Heinrich, Shantenu Jha, Daniel S. Katz, Volodymyr V. Kindratenko, Christine R. Kirkpatrick, Kati Lassila-Perini, Ravi K. Madduri, Mark S. Neubauer, Fotis E. Psomopoulos, Avik Roy, Oliver Rübel, Zhizhen Zhao, Ruike Zhu
FAIR for AI: An interdisciplinary, international, inclusive, and diverse community building perspective. CoRR (2022)
Jan Balewski, Zhenying Liu, Alexander Tsyplikhin, Manuel Lopez Roland, Kristofer E. Bouchard
Time-series ML-regression on Graphcore IPU-M2000 and Nvidia A100. PMBS@SC (2022)
Jesse A. Livezey, Ahyeon Hwang, Jacob Yeung, Kristofer E. Bouchard
Hangul Fonts Dataset: A Hierarchical and Compositional Dataset for Investigating Learned Representations. ICIAP (3) (2022)
Alexander Ladd, Kyung Geun Kim, Jan Balewski, Kristofer E. Bouchard, Roy Ben-Shalom
Scaling and Benchmarking an Evolutionary Algorithm for Constructing Biophysical Neuronal Models. Frontiers Neuroinformatics 16 (2022)
Rui Meng, Tianyi Luo, Kristofer E. Bouchard
Compressed Predictive Information Coding. CoRR (2022)
Rui Meng, Herbie Lee, Kristofer E. Bouchard
Collaborative Nonstationary Multivariate Gaussian Process Model. CoRR (2021)
John Hermiz, Elias Joseph, Kyu Hyun Lee, Isabella A. Baldacci, Jason E. Chung, Loren M. Frank, Kristofer E. Bouchard, Peter Denes
The impact of reducing signal acquisition specifications on neuronal spike sorting. EMBC (2021)
Luca Pion-Tonachini, Kristofer E. Bouchard, Héctor García Martín, Sean Peisert, W. Bradley Holtz, Anil Aswani, Dipankar Dwivedi, Haruko M. Wainwright, Ghanshyam Pilania, Benjamin Nachman, Babetta L. Marrone, Nicola Falco, Prabhat, Daniel B. Arnold, Alejandro Wolf-Yadlin, Sarah Powers, Sharlee Climer, Quinn Jackson, Ty Carlson, Michael Sohn, Petrus H. Zwart, Neeraj Kumar, Amy Justice, Claire J. Tomlin, Daniel A. Jacobson, Gos Micklem, Georgios V. Gkoutos, Peter J. Bickel, Jean-Baptiste Cazier, Juliane Müller, Bobbie-Jo Webb-Robertson, Rick Stevens, Mark Anderson, Kenneth Kreutz-Delgado, Michael W. Mahoney, James B. Brown
Learning from learning machines: a new generation of AI technology to meet the needs of science. CoRR (2021)
Charles G. Frye, James Simon, Neha S. Wadia, Andrew Ligeralde, Michael Robert DeWeese, Kristofer E. Bouchard
Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses. Neural Comput. 33 (6) (2021)
Rui Meng, Kristofer E. Bouchard
Bayesian Inference in High-Dimensional Time-Serieswith the Orthogonal Stochastic Linear Mixing Model. CoRR (2021)
Sugeerth Murugesan, Kristofer E. Bouchard, Jesse A. Brown, Mariam Kiran, Dan Lurie, Bernd Hamann, Gunther H. Weber
State-based network similarity visualization. Inf. Vis. 19 (2) (2020)
Charles G. Frye, James Simon, Neha S. Wadia, Andrew Ligeralde, Michael Robert DeWeese, Kristofer E. Bouchard
Critical Point-Finding Methods Reveal Gradient-Flat Regions of Deep Network Losses. CoRR (2020)
Mahesh Balasubramanian, Trevor D. Ruiz, Brandon Cook, Prabhat, Sharmodeep Bhattacharyya, Aviral Shrivastava, Kristofer E. Bouchard
Scaling of Union of Intersections for Inference of Granger Causal Networks from Observational Data. IPDPS (2020)
Trevor D. Ruiz, Sharmodeep Bhattacharyya, Mahesh Balasubramanian, Kristofer E. Bouchard
Sparse and Low-bias Estimation of High Dimensional Vector Autoregressive Models. L4DC (2020)
Pratik S. Sachdeva, Jesse Livezey, Andrew J. Tritt, Kristofer E. Bouchard
PyUoI: The Union of Intersections Framework in Python. J. Open Source Softw. 4 (44) (2019)
Jesse A. Livezey, Ahyeon Hwang, Kristofer E. Bouchard
Hangul Fonts Dataset: a Hierarchical and Compositional Dataset for Interrogating Learned Representations. CoRR (2019)
David G. Clark, Jesse Livezey, Kristofer E. Bouchard
Unsupervised Discovery of Temporal Structure in Noisy Data with Dynamical Components Analysis. NeurIPS (2019)
Jesse A. Livezey, Kristofer E. Bouchard, Edward F. Chang
Deep learning as a tool for neural data analysis: Speech classification and cross-frequency coupling in human sensorimotor cortex. PLoS Comput. Biol. 15 (9) (2019)
David G. Clark, Jesse A. Livezey, Kristofer E. Bouchard
Unsupervised Discovery of Temporal Structure in Noisy Data with Dynamical Components Analysis. CoRR (2019)
Andrew J. Tritt, Oliver Rübel, Benjamin K. Dichter, Ryan Ly, Donghe Kang, Edward F. Chang, Loren M. Frank, Kristofer E. Bouchard
HDMF: Hierarchical Data Modeling Framework for Modern Science Data Standards. IEEE BigData (2019)
Maximilian E. Dougherty, Anh P. Q. Nguyen, Vyassa L. Baratham, Kristofer E. Bouchard
Laminar origin of evoked ECoG high-gamma activity. EMBC (2019)
Charles G. Frye, Neha S. Wadia, Michael Robert DeWeese, Kristofer E. Bouchard
Numerically Recovering the Critical Points of a Deep Linear Autoencoder. CoRR (2019)
Pratik S. Sachdeva, Sharmodeep Bhattacharyya, Kristofer E. Bouchard
Sparse, Predictive, and Interpretable Functional Connectomics with UoILasso. EMBC (2019)
Jesse A. Livezey, Kristofer E. Bouchard, Edward F. Chang
Deep learning as a tool for neural data analysis: speech classification and cross-frequency coupling in human sensorimotor cortex. CoRR (2018)
Anastasios Kyrillidis, Shashanka Ubaru, Georgios Kollias, Kristofer E. Bouchard
Run Procrustes, Run! On the convergence of accelerated Procrustes Flow. CoRR (2018)
Kristofer E. Bouchard, James B. Aimone, Miyoung Chun, Thomas Dean, Michael Denker, Markus Diesmann, David Donofrio, Loren M. Frank, Narayanan Kasthuri, Christof Koch, Oliver Rübel, Horst D. Simon, Friedrich T. Sommer, Prabhat
International Neuroscience Initiatives through the Lens of High-Performance Computing. Computer 51 (4) (2018)
Mahesh Balasubramanian, Trevor D. Ruiz, Brandon Cook, Sharmodeep Bhattacharyya, Prabhat, Aviral Shrivastava, Kristofer E. Bouchard
) Algorithms for Improved Statistical Estimation at Scale. CoRR (2018)
David G. Clark, Jesse A. Livezey, Edward F. Chang, Kristofer E. Bouchard
Spiking Linear Dynamical Systems on Neuromorphic Hardware for Low-Power Brain-Machine Interfaces. CoRR (2018)
Sugeerth Murugesan, Kristofer E. Bouchard, Edward F. Chang, Max Dougherty, Bernd Hamann, Gunther H. Weber
Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions. BMC Bioinform. 18 (6) (2017)
Sugeerth Murugesan, Kristofer E. Bouchard, Jesse A. Brown, Bernd Hamann, William W. Seeley, Andrew Trujillo, Gunther H. Weber
Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity. IEEE ACM Trans. Comput. Biol. Bioinform. 14 (4) (2017)
Shashanka Ubaru, Kesheng Wu, Kristofer E. Bouchard
UoI-NMF Cluster: A Robust Nonnegative Matrix Factorization Algorithm for Improved Parts-Based Decomposition and Reconstruction of Noisy Data. ICMLA (2017)
Kristofer E. Bouchard, Alejandro F. Bujan, Farbod Roosta-Khorasani, Shashanka Ubaru, Prabhat, Antoine Snijders, Jian-Hua Mao, Edward F. Chang, Michael W. Mahoney, Sharmodeep Bhattacharyya
Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction. NIPS (2017)
Kristofer E. Bouchard, Alejandro F. Bujan, Edward F. Chang, Friedrich T. Sommer
Sparse coding of ECoG signals identifies interpretable components for speech control in human sensorimotor cortex. EMBC (2017)
Houjun Tang, Surendra Byna, Steve Harenberg, Xiaocheng Zou, Wenzhao Zhang, Kesheng Wu, Bin Dong, Oliver Rübel, Kristofer E. Bouchard, Scott Klasky, Nagiza F. Samatova
Usage Pattern-Driven Dynamic Data Layout Reorganization. CCGrid (2016)
Oliver Rübel, Max Dougherty, Prabhat, Peter Denes, David Conant, Edward F. Chang, Kristofer E. Bouchard
Methods for Specifying Scientific Data Standards and Modeling Relationships with Applications to Neuroscience. Frontiers Neuroinformatics 10 (2016)
Sugeerth Murugesan, Kristofer E. Bouchard, Edward F. Chang, Max Dougherty, Bernd Hamann, Gunther H. Weber
Hierarchical Spatio-temporal Visual Analysis of Cluster Evolution in Electrocorticography Data. BCB (2016)
Jason D. Wittenbach, Kristofer E. Bouchard, Michael S. Brainard, Dezhe Z. Jin
An Adapting Auditory-motor Feedback Loop Can Contribute to Generating Vocal Repetition. PLoS Comput. Biol. 11 (10) (2015)
Kristofer E. Bouchard, Surya Ganguli, Michael S. Brainard
Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences. Frontiers Comput. Neurosci. 9 (2015)
Kristofer E. Bouchard, Edward F. Chang
Neural decoding of spoken vowels from human sensory-motor cortex with high-density electrocorticography. EMBC (2014)