Brian Matejek

According to our database, Brian Matejek authored at least 22 papers between 2015 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Breaking Bad: Interpretability-Based Safety Audits of State-of-the-Art LLMs.

Krishiv Agarwal, Ramneet Kaur, Colin Samplawski, Manoj Acharya, Anirban Roy, Daniel Elenius, Brian Matejek, Adam D. Cobb, Susmit Jha

CoRR, April, 2026

Do Diffusion Models Dream of Electric Planes? Discrete and Continuous Simulation-Based Inference for Aircraft Design.

Aurelien Ghiglino, Daniel Elenius, Anirban Roy, Ramneet Kaur, Manoj Acharya, Colin Samplawski, Brian Matejek, Susmit Jha, Juan Alonso, Adam D. Cobb

CoRR, March, 2026

2025

Spatio-Temporal Pruning for Compressed Spiking Large Language Models.

Yi Jiang, Malyaban Bal, Brian Matejek, Susmit Jha, Adam D. Cobb, Abhronil Sengupta

CoRR, August, 2025

Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding.

Trilok Padhi, Ramneet Kaur, Adam D. Cobb, Manoj Acharya, Anirban Roy, Colin Samplawski, Brian Matejek, Alexander M. Berenbeim, Nathaniel D. Bastian, Susmit Jha

CoRR, May, 2025

SAFE-NID: Self-Attention with Normalizing-Flow Encodings for Network Intrusion Detection.

Brian Matejek, Ashish Gehani, Nathaniel D. Bastian, Daniel J. Clouse, Bradford J. Kline, Susmit Jha

Trans. Mach. Learn. Res., 2025

Melanoma Detection with Uncertainty Quantification.

Sanghyuk Kim, Edward Gaibor, Brian Matejek, Daniel Haehn

Proceedings of the 22nd IEEE International Symposium on Biomedical Imaging, 2025

2024

Addressing Uncertainty in LLMs to Enhance Reliability in Generative AI.

Ramneet Kaur, Colin Samplawski, Adam D. Cobb, Anirban Roy, Brian Matejek, Manoj Acharya, Daniel Elenius, Alexander M. Berenbeim, John A. Pavlik, Nathaniel D. Bastian, Susmit Jha

CoRR, 2024

Resource-Constrained Heuristic for Max-SAT.

Brian Matejek, Daniel Elenius, Cale Gentry, David Stoker, Adam D. Cobb

CoRR, 2024

Non-Invasive Stress Monitoring From Video.

Akshata Tiwari, Brian Matejek, Daniel Haehn

Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Direct Amortized Likelihood Ratio Estimation.

Adam D. Cobb, Brian Matejek, Daniel Elenius, Anirban Roy, Susmit Jha

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2022

Scalable Biologically-Aware Skeleton Generation for Connectomic Volumes.

Brian Matejek, Tim Franzmeyer, Donglai Wei, Xueying Wang, Jinglin Zhao, Kálmán Palágyi, Jeff W. Lichtman, Hanspeter Pfister

IEEE Trans. Medical Imaging, 2022

Algorithmic Tools for Understanding the Motif Structure of Networks.

Tianyi Chen, Brian Matejek, Michael Mitzenmacher, Charalampos E. Tsourakakis

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

2021

AxonEM Dataset: 3D Axon Instance Segmentation of Brain Cortical Regions.

Donglai Wei, Kisuk Lee, Hanyu Li, Ran Lu, J. Alexander Bae, Zequan Liu, Lifu Zhang, Márcia dos Santos, Zudi Lin, Thomas D. Uram, Xueying Wang, Ignacio Arganda-Carreras, Brian Matejek, Narayanan Kasthuri, Jeff Lichtman, Hanspeter Pfister

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

2020

Two Stream Active Query Suggestion for Active Learning in Connectomics.

Zudi Lin, Donglai Wei, Won-Dong Jang, Siyan Zhou, Xupeng Chen, Xueying Wang, Richard Schalek, Daniel R. Berger, Brian Matejek, Lee Kamentsky, Adi Suissa-Peleg, Daniel Haehn, Thouis R. Jones, Toufiq Parag, Jeff Lichtman, Hanspeter Pfister

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

Commercial Visual Analytics Systems-Advances in the Big Data Analytics Field.

Michael Behrisch, Dirk Streeb, Florian Stoffel, Daniel Seebacher, Brian Matejek, Stefan Hagen Weber, Sebastian Mittelstädt, Hanspeter Pfister, Daniel A. Keim

IEEE Trans. Vis. Comput. Graph., 2019

Synapse-Aware Skeleton Generation for Neural Circuits.

Brian Matejek, Donglai Wei, Xueying Wang, Jinglin Zhao, Kálmán Palágyi, Hanspeter Pfister

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Biologically-Constrained Graphs for Global Connectomics Reconstruction.

Brian Matejek, Daniel Haehn, Haidong Zhu, Donglai Wei, Toufiq Parag, Hanspeter Pfister

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Efficient Correction for EM Connectomics with Skeletal Representation.

Konstantin Dimitriev, Toufiq Parag, Brian Matejek, Arie E. Kaufman, Hanspeter Pfister

Proceedings of the British Machine Vision Conference 2018, 2018

2017

Scalable Interactive Visualization for Connectomics.

Daniel Haehn, John Hoffer, Brian Matejek, Adi Suissa-Peleg, Ali K. Al-Awami, Lee Kamentsky, Felix Gonda, Eagon Meng, William Zhang, Richard Schalek, Alyssa Wilson, Toufiq Parag, Johanna Beyer, Verena Kaynig, Thouis R. Jones, James Tompkin, Markus Hadwiger, Jeff W. Lichtman, Hanspeter Pfister

Informatics, 2017

Anisotropic EM Segmentation by 3D Affinity Learning and Agglomeration.

Toufiq Parag, Fabian Tschopp, William Grisaitis, Srinivas C. Turaga, Xuewen Zhang, Brian Matejek, Lee Kamentsky, Jeff W. Lichtman, Hanspeter Pfister

CoRR, 2017

Compresso: Efficient Compression of Segmentation Data for Connectomics.

Brian Matejek, Daniel Haehn, Fritz Lekschas, Michael Mitzenmacher, Hanspeter Pfister

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

2015

Learning Hierarchical Semantic Segmentations of LIDAR Data.

David Dohan, Brian Matejek, Thomas A. Funkhouser

Proceedings of the 2015 International Conference on 3D Vision, 2015