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Timo Bremer
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- affiliation: Lawrence Livermore National Laboratory, Livermore, CA, USA
- affiliation (former): University of California, Davis, USA
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2020 – today
- 2024
[j80]Shusen Liu, Haichao Miao
, Zhimin Li, Matthew L. Olson, Valerio Pascucci, Peer-Timo Bremer:
AVA: Towards Autonomous Visualization Agents through Visual Perception-Driven Decision-Making. Comput. Graph. Forum 43(3) (2024)- [j79]Lanya T. Cai, Joseph Y. Moon, Paul B. Camacho, Aaron T. Anderson, Won Jong Chwa, Bradley P. Sutton, Amy J. Markowitz, Eva M. Palacios, Alexis A. Rodriguez, Geoffrey T. Manley, Shivsundaram Shankar, Peer-Timo Bremer, Pratik Mukherjee, Ravi K. Madduri, Shankar Gopinath, Ramesh Grandhi, C. Dirk Keene, Michael A. McCrea, Randall Merchant, Laura B. Ngwenya, Ava M. Puccio, David Schnyer, Sabrina R. Taylor, John K. Yue, Esther L. Yuh, Ross Zafonte:
MaPPeRTrac: A Massively Parallel, Portable, and Reproducible Tractography Pipeline. Neuroinformatics 22(2): 177-191 (2024) - [j78]Zhimin Li, Harshitha Menon, Kathryn M. Mohror, Shusen Liu, Luanzheng Guo, Peer-Timo Bremer, Valerio Pascucci:
A Visual Comparison of Silent Error Propagation. IEEE Trans. Vis. Comput. Graph. 30(7): 3268-3282 (2024) - [c84]Vuthea Chheang, Brian Thomas Weston, Robert William Cerda, Brian Au, Brian Giera, Peer-Timo Bremer, Haichao Miao:
A Virtual Environment for Collaborative Inspection in Additive Manufacturing. CHI Extended Abstracts 2024: 26:1-26:7 - [i45]Vuthea Chheang, Brian Thomas Weston, Robert William Cerda, Brian Au, Brian Giera, Peer-Timo Bremer, Haichao Miao:
A Virtual Environment for Collaborative Inspection in Additive Manufacturing. CoRR abs/2403.08940 (2024) - [i44]Vuthea Chheang, Saurabh Narain, Garrett Hooten, Robert William Cerda, Brian Au, Brian Thomas Weston, Brian Giera, Peer-Timo Bremer, Haichao Miao:
Enabling Additive Manufacturing Part Inspection of Digital Twins via Collaborative Virtual Reality. CoRR abs/2405.12931 (2024) - [i43]Zane Fink, Konstantinos Parasyris, Praneet Rathi, Giorgis Georgakoudis, Harshitha Menon, Peer-Timo Bremer:
HPAC-ML: A Programming Model for Embedding ML Surrogates in Scientific Applications. CoRR abs/2407.18352 (2024) - [i42]Xuan Huang, Haichao Miao, Hyojin Kim, Andrew Townsend, Kyle Champley, Joseph W. Tringe, Valerio Pascucci, Peer-Timo Bremer:
Bimodal Visualization of Industrial X-Ray and Neutron Computed Tomography Data. CoRR abs/2408.11957 (2024) - 2023
- [j77]Michela Taufer, Heberth F. Martinez, Jakob Lüttgau, Lauren Whitnah, Giorgio Scorzelli, Pania Newell, Aashish Panta, Peer-Timo Bremer, Douglas Fils, Christine R. Kirkpatrick, Valerio Pascucci:
Enhancing Scientific Research with FAIR Digital Objects in the National Science Data Fabric. Comput. Sci. Eng. 25(5): 39-47 (2023) - [j76]Suraj P. Kesavan, Harsh Bhatia, Abhinav Bhatele, Stephanie Brink, Olga Pearce, Todd Gamblin, Peer-Timo Bremer, Kwan-Liu Ma:
Scalable Comparative Visualization of Ensembles of Call Graphs. IEEE Trans. Vis. Comput. Graph. 29(3): 1691-1704 (2023) - [c83]Matthew L. Olson, Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Weng-Keen Wong:
Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences Between Pretrained Generative Models. CVPR 2023: 7981-7990 - [c82]Peer-Timo Bremer, Kristi Potter, Steffen Frey, Silvio Rizzi, Gunther H. Weber, Soumya Dutta, Jonas Lukasczyk, Nicole Marsiglia:
Preface IEEE LDAV 2023. LDAV 2023: vi - [i41]Matthew L. Olson, Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Weng-Keen Wong:
Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences between Pretrained Generative Models. CoRR abs/2303.10774 (2023) - [i40]Rafael Ferreira da Silva, Rosa M. Badia, Venkat Bala, Debbie Bard, Peer-Timo Bremer, Ian Buckley, Silvina Caíno-Lores, Kyle Chard, Carole A. Goble, Shantenu Jha, Daniel S. Katz, Daniel E. Laney, Manish Parashar, Frédéric Suter, Nick Tyler, Thomas D. Uram, Ilkay Altintas, Stefan Andersson, William Arndt, Juan Aznar, Jonathan Bader, Bartosz Balis, Chris Blanton, Kelly Rosa Braghetto, Aharon Brodutch, Paul Brunk, Henri Casanova, Alba Cervera-Lierta, Justin Chigu, Tainã Coleman, Nick Collier, Iacopo Colonnelli, Frederik Coppens, Michael R. Crusoe, Will Cunningham, Bruno de Paula Kinoshita, Paolo Di Tommaso, Charles M. Doutriaux, Matthew Downton, Wael R. Elwasif, Bjoern Enders, Chris Erdmann, Thomas Fahringer, Ludmilla Figueiredo, Rosa Filgueira, Martin Foltin, Anne Fouilloux, Luiz Gadelha, Andy Gallo, Artur García-Sáez, et al.:
Workflows Community Summit 2022: A Roadmap Revolution. CoRR abs/2304.00019 (2023) - [i39]Zhimin Li, Shusen Liu, Bhavya Kailkhura, Timo Bremer, Valerio Pascucci:
Instance-wise Linearization of Neural Network for Model Interpretation. CoRR abs/2310.16295 (2023) - [i38]Seung-Won Suh, Seung Whan Chung, Peer-Timo Bremer, Youngsoo Choi:
Accelerating Flow Simulations using Online Dynamic Mode Decomposition. CoRR abs/2311.18715 (2023) - [i37]Shusen Liu, Haichao Miao, Zhimin Li, Matthew L. Olson, Valerio Pascucci, Peer-Timo Bremer:
AVA: Towards Autonomous Visualization Agents through Visual Perception-Driven Decision-Making. CoRR abs/2312.04494 (2023) - [i36]Peer-Timo Bremer, Brian K. Spears, Tom Gibbs, Michael Bussmann:
AI-Augmented Facilities: Bridging Experiment and Simulation with ML (Dagstuhl Seminar 23132). Dagstuhl Reports 13(3): 106-131 (2023) - 2022
- [j75]J. Luc Peterson, Benjamin Bay, Joe Koning, Peter B. Robinson, Jessica Semler, Jeremy White, Rushil Anirudh, Kevin Athey, Peer-Timo Bremer, Francesco Di Natale, David Fox, Jim A. Gaffney, Sam Ade Jacobs, Bhavya Kailkhura, Bogdan Kustowski, Steve H. Langer, Brian K. Spears, Jayaraman J. Thiagarajan, Brian Van Essen, Jae-Seung Yeom:
Enabling machine learning-ready HPC ensembles with Merlin. Future Gener. Comput. Syst. 131: 255-268 (2022) - [j74]Joseph Y. Moon, Pratik Mukherjee, Ravi K. Madduri, Amy J. Markowitz, Lanya T. Cai, Eva M. Palacios, Geoffrey T. Manley, Peer-Timo Bremer:
The Case for Optimized Edge-Centric Tractography at Scale. Frontiers Neuroinformatics 16: 752471 (2022) - [j73]Bogdan Kustowski, Jim A. Gaffney, Brian K. Spears, Gemma J. Anderson, Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan, Michael K. G. Kruse, Ryan Nora:
Suppressing simulation bias in multi-modal data using transfer learning. Mach. Learn. Sci. Technol. 3(1): 15035 (2022) - [j72]Harsh Bhatia, Jayaraman J. Thiagarajan, Rushil Anirudh, T. S. Jayram, Tomas Oppelstrup, Helgi I. Ingólfsson, Felice C. Lightstone, Peer-Timo Bremer:
A biology-informed similarity metric for simulated patches of human cell membrane. Mach. Learn. Sci. Technol. 3(3): 35010 (2022) - [j71]Aniketh Venkat, Attila Gyulassy, Graham Kosiba, Amitesh Maiti, Henry Reinstein, Richard Gee, Peer-Timo Bremer, Valerio Pascucci:
Towards replacing physical testing of granular materials with a Topology-based Model. IEEE Trans. Vis. Comput. Graph. 28(1): 76-85 (2022) - [j70]Harsh Bhatia, Duong Hoang, Nate Morrical, Valerio Pascucci, Peer-Timo Bremer, Peter Lindstrom:
AMM: Adaptive Multilinear Meshes. IEEE Trans. Vis. Comput. Graph. 28(6): 2350-2363 (2022) - [c81]Pavol Klacansky, Haichao Miao, Attila Gyulassy, Andrew Townsend, Kyle Champley, Joseph W. Tringe, Valerio Pascucci, Peer-Timo Bremer:
Virtual Inspection of Additively Manufactured Parts. PacificVis 2022: 81-90 - [c80]Pavol Klacansky, Attila Gyulassy, Peer-Timo Bremer, Valerio Pascucci:
A Study of the Locality of Persistence-Based Queries and Its Implications for the Efficiency of Localized Data Structures. PacificVis 2022: 121-130 - [c79]Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer:
Sparsity Improves Unsupervised Attribute Discovery in Stylegan. ICASSP 2022: 3388-3392 - [c78]Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz:
Accurate Calibration of Agent-based Epidemiological Models with Neural Network Surrogates. Healthcare AI and COVID-19 Workshop 2022: 54-62 - [c77]Jayaraman J. Thiagarajan, Rushil Anirudh, Peer-Timo Bremer, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz:
Machine Learning-Powered Mitigation Policy Optimization in Epidemiological Models. Healthcare AI and COVID-19 Workshop 2022: 63-72 - [c76]Aniketh Venkat, Duong Hoang, Attila Gyulassy, Peer-Timo Bremer, Frederick Federer, Alessandra Angelucci, Valerio Pascucci:
High-Quality Progressive Alignment of Large 3D Microscopy Data. LDAV 2022: 1-10 - [c75]Sara Fridovich-Keil, Brian R. Bartoldson, James Diffenderfer, Bhavya Kailkhura, Timo Bremer:
Models Out of Line: A Fourier Lens on Distribution Shift Robustness. NeurIPS 2022 - [c74]Jayaraman J. Thiagarajan, Rushil Anirudh, Vivek Sivaraman Narayanaswamy, Timo Bremer:
Single Model Uncertainty Estimation via Stochastic Data Centering. NeurIPS 2022 - [i35]Zhimin Li, Shusen Liu, Xin Yu, Bhavya Kailkhura, Jie Cao, James Daniel Diffenderfer, Peer-Timo Bremer, Valerio Pascucci:
"Understanding Robustness Lottery": A Comparative Visual Analysis of Neural Network Pruning Approaches. CoRR abs/2206.07918 (2022) - [i34]Sara Fridovich-Keil, Brian R. Bartoldson, James Diffenderfer, Bhavya Kailkhura, Peer-Timo Bremer:
Models Out of Line: A Fourier Lens on Distribution Shift Robustness. CoRR abs/2207.04075 (2022) - [i33]Konstantia Georgouli, Helgi I. Ingólfsson, Fikret Aydin, Mark Heimann, Felice C. Lightstone, Peer-Timo Bremer, Harsh Bhatia:
Emerging Patterns in the Continuum Representation of Protein-Lipid Fingerprints. CoRR abs/2207.04333 (2022) - [i32]Fikret Aydin, Konstantia Georgouli, Gautham Dharuman, James N. Glosli, Felice C. Lightstone, Helgi I. Ingólfsson, Peer-Timo Bremer, Harsh Bhatia:
Identifying Orientation-specific Lipid-protein Fingerprints using Deep Learning. CoRR abs/2207.06630 (2022) - [i31]Jayaraman J. Thiagarajan, Rushil Anirudh, Vivek Sivaraman Narayanaswamy, Peer-Timo Bremer:
Single Model Uncertainty Estimation via Stochastic Data Centering. CoRR abs/2207.07235 (2022) - 2021
- [j69]Torin McDonald, Rebika Shrestha, Xiyu Yi, Harsh Bhatia, De Chen, Debanjan Goswami, Valerio Pascucci, Thomas Turbyville, Peer-Timo Bremer:
Leveraging Topological Events in Tracking Graphs for Understanding Particle Diffusion. Comput. Graph. Forum 40(3): 251-262 (2021) - [j68]Rushil Anirudh, Jayaraman J. Thiagarajan, Rahul Sridhar, Peer-Timo Bremer:
MARGIN: Uncovering Deep Neural Networks Using Graph Signal Analysis. Frontiers Big Data 4: 589417 (2021) - [j67]Harsh Bhatia, Timothy S. Carpenter, Helgi I. Ingólfsson, Gautham Dharuman, Piyush Karande, Shusen Liu, Tomas Oppelstrup, Chris Neale, Felice C. Lightstone, Brian Van Essen, James N. Glosli, Peer-Timo Bremer:
Machine-learning-based dynamic-importance sampling for adaptive multiscale simulations. Nat. Mach. Intell. 3(5): 401-409 (2021) - [j66]Gowtham Muniraju, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Cihan Tepedelenlioglu, Andreas Spanias:
Coverage-Based Designs Improve Sample Mining and Hyperparameter Optimization. IEEE Trans. Neural Networks Learn. Syst. 32(3): 1241-1253 (2021) - [j65]Duong Hoang, Brian Summa, Harsh Bhatia, Peter Lindstrom, Pavol Klacansky, Will Usher, Peer-Timo Bremer, Valerio Pascucci:
Efficient and Flexible Hierarchical Data Layouts for a Unified Encoding of Scalar Field Precision and Resolution. IEEE Trans. Vis. Comput. Graph. 27(2): 603-613 (2021) - [j64]Huu Tan Nguyen, Abhinav Bhatele, Nikhil Jain, Suraj P. Kesavan, Harsh Bhatia, Todd Gamblin, Kwan-Liu Ma, Peer-Timo Bremer:
Visualizing Hierarchical Performance Profiles of Parallel Codes Using CallFlow. IEEE Trans. Vis. Comput. Graph. 27(4): 2455-2468 (2021) - [j63]Harsh Bhatia, Robert M. Kirby, Valerio Pascucci, Peer-Timo Bremer:
Vector Field Decompositions Using Multiscale Poisson Kernel. IEEE Trans. Vis. Comput. Graph. 27(9): 3781-3793 (2021) - [j62]Zhimin Li, Harshitha Menon, Dan Maljovec, Yarden Livnat, Shusen Liu, Kathryn M. Mohror, Peer-Timo Bremer, Valerio Pascucci:
SpotSDC: Revealing the Silent Data Corruption Propagation in High-Performance Computing Systems. IEEE Trans. Vis. Comput. Graph. 27(10): 3938-3952 (2021) - [c73]Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Peer-Timo Bremer, Andreas Spanias:
Accurate and Robust Feature Importance Estimation under Distribution Shifts. AAAI 2021: 7891-7898 - [c72]Xuan Huang, Pavol Klacansky, Steve Petruzza, Attila Gyulassy, Peer-Timo Bremer, Valerio Pascucci:
Distributed merge forest: a new fast and scalable approach for topological analysis at scale. ICS 2021: 367-377 - [c71]Harsh Bhatia, Steve Petruzza, Rushil Anirudh, Attila Gyulassy, Robert M. Kirby, Valerio Pascucci, Peer-Timo Bremer:
Data-Driven Estimation of Temporal-Sampling Errors in Unsteady Flows. ISVC (1) 2021: 235-248 - [c70]Sergei Shudler, Steve Petruzza, Valerio Pascucci, Peer-Timo Bremer:
Portable and Composable Flow Graphs for In Situ Analytics. LDAV 2021: 63-72 - [c69]Zhimin Li, Harshitha Menon, Kathryn M. Mohror, Peer-Timo Bremer, Yarden Livnat, Valerio Pascucci:
Understanding a program's resiliency through error propagation. PPoPP 2021: 362-373 - [c68]Harsh Bhatia, Francesco Di Natale, Joseph Y. Moon, Xiaohua Zhang, Joseph R. Chavez, Fikret Aydin, Christopher B. Stanley, Tomas Oppelstrup, Chris Neale, Sara Kokkila Schumacher, Dong H. Ahn, Stephen Herbein, Timothy S. Carpenter, Sandrasegaram Gnanakaran, Peer-Timo Bremer, James N. Glosli, Felice C. Lightstone, Helgi I. Ingólfsson:
Generalizable coordination of large multiscale workflows: challenges and learnings at scale. SC 2021: 10 - [i30]Bogdan Kustowski, Jim A. Gaffney, Brian K. Spears, Gemma J. Anderson, Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan:
Transfer learning suppresses simulation bias in predictive models built from sparse, multi-modal data. CoRR abs/2104.09684 (2021) - [i29]Ankita Shukla, Rushil Anirudh, Eugene Kur, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Brian K. Spears, Tammy Ma, Pavan K. Turaga:
Geometric Priors for Scientific Generative Models in Inertial Confinement Fusion. CoRR abs/2111.12798 (2021) - 2020
- [j61]Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Peer-Timo Bremer:
MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking. Int. J. Comput. Vis. 128(10): 2459-2477 (2020) - [j60]Hank Childs, Sean Ahern, James P. Ahrens, Andrew C. Bauer, Janine Bennett, E. Wes Bethel, Peer-Timo Bremer, Eric Brugger, Joseph Cottam, Matthieu Dorier, Soumya Dutta, Jean M. Favre, Thomas Fogal, Steffen Frey, Christoph Garth, Berk Geveci, William F. Godoy, Charles D. Hansen, Cyrus Harrison, Bernd Hentschel, Joseph A. Insley, Christopher R. Johnson, Scott Klasky, Aaron Knoll, James Kress, Matthew Larsen, Jay F. Lofstead, Kwan-Liu Ma, Preeti Malakar, Jeremy S. Meredith, Kenneth Moreland, Paul A. Navrátil, Patrick O'Leary, Manish Parashar, Valerio Pascucci, John Patchett, Tom Peterka, Steve Petruzza, Norbert Podhorszki, David Pugmire, Michel E. Rasquin, Silvio Rizzi, David H. Rogers, Sudhanshu Sane, Franz Sauer, Robert Sisneros, Han-Wei Shen, Will Usher, Rhonda Vickery, Venkatram Vishwanath, Ingo Wald, Ruonan Wang, Gunther H. Weber, Brad Whitlock, Matthew Wolf, Hongfeng Yu, Sean B. Ziegeler:
A terminology for in situ visualization and analysis systems. Int. J. High Perform. Comput. Appl. 34(6) (2020) - [j59]Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer:
Uncovering interpretable relationships in high-dimensional scientific data through function preserving projections. Mach. Learn. Sci. Technol. 1(4): 45016 (2020) - [j58]Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Brian K. Spears:
Improved surrogates in inertial confinement fusion with manifold and cycle consistencies. Proc. Natl. Acad. Sci. USA 117(18): 9741-9746 (2020) - [j57]Pavol Klacansky, Attila Gyulassy, Peer-Timo Bremer, Valerio Pascucci:
Toward Localized Topological Data Structures: Querying the Forest for the Tree. IEEE Trans. Vis. Comput. Graph. 26(1): 173-183 (2020) - [j56]Shusen Liu, Jim Gaffney, J. Luc Peterson, Peter B. Robinson, Harsh Bhatia, Valerio Pascucci, Brian K. Spears, Peer-Timo Bremer, Di Wang, Dan Maljovec, Rushil Anirudh, Jayaraman J. Thiagarajan, Sam Ade Jacobs, Brian C. Van Essen, David Hysom, Jae-Seung Yeom:
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. IEEE Trans. Vis. Comput. Graph. 26(1): 291-300 (2020) - [c67]Jayaraman J. Thiagarajan, Bindya Venkatesh, Prasanna Sattigeri, Peer-Timo Bremer:
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors. AAAI 2020: 6005-6012 - [c66]Bhavya Kailkhura, Jayaraman J. Thiagarajan, Qunwei Li, Jize Zhang, Yi Zhou, Timo Bremer:
A Statistical Mechanics Framework for Task-Agnostic Sample Design in Machine Learning. NeurIPS 2020 - [i28]Jayaraman J. Thiagarajan, Bindya Venkatesh, Rushil Anirudh, Peer-Timo Bremer, Jim Gaffney, Gemma Anderson, Brian K. Spears:
Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models. CoRR abs/2005.02328 (2020) - [i27]Suraj P. Kesavan, Harsh Bhatia, Abhinav Bhatele, Todd Gamblin, Peer-Timo Bremer, Kwan-Liu Ma:
Scalable Comparative Visualization of Ensembles of Call Graphs. CoRR abs/2007.01395 (2020) - [i26]Harsh Bhatia, Duong Hoang, Garrett Morrison, Will Usher, Valerio Pascucci, Peer-Timo Bremer, Peter Lindstrom:
AMM: Adaptive Multilinear Meshes. CoRR abs/2007.15219 (2020) - [i25]Jayaraman J. Thiagarajan, Vivek Sivaraman Narayanaswamy, Rushil Anirudh, Peer-Timo Bremer, Andreas Spanias:
Accurate and Robust Feature Importance Estimation under Distribution Shifts. CoRR abs/2009.14454 (2020) - [i24]Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz:
Accurate Calibration of Agent-based Epidemiological Models with Neural Network Surrogates. CoRR abs/2010.06558 (2020) - [i23]Jayaraman J. Thiagarajan, Peer-Timo Bremer, Rushil Anirudh, Timothy C. Germann, Sara Y. Del Valle, Frederick H. Streitz:
Machine Learning-Powered Mitigation Policy Optimization in Epidemiological Models. CoRR abs/2010.08478 (2020) - [i22]Gemma J. Anderson, Jim A. Gaffney, Brian K. Spears, Peer-Timo Bremer, Rushil Anirudh, Jayaraman J. Thiagarajan:
Meaningful uncertainties from deep neural network surrogates of large-scale numerical simulations. CoRR abs/2010.13749 (2020)
2010 – 2019
- 2019
- [j55]Shusen Liu, Zhimin Li, Tao Li, Vivek Srikumar, Valerio Pascucci, Peer-Timo Bremer:
NLIZE: A Perturbation-Driven Visual Interrogation Tool for Analyzing and Interpreting Natural Language Inference Models. IEEE Trans. Vis. Comput. Graph. 25(1): 651-660 (2019) - [j54]Attila Gyulassy, Peer-Timo Bremer, Valerio Pascucci:
Shared-Memory Parallel Computation of Morse-Smale Complexes with Improved Accuracy. IEEE Trans. Vis. Comput. Graph. 25(1): 1183-1192 (2019) - [j53]Duong Hoang, Pavol Klacansky, Harsh Bhatia, Peer-Timo Bremer, Peter Lindstrom, Valerio Pascucci:
A Study of the Trade-off Between Reducing Precision and Reducing Resolution for Data Analysis and Visualization. IEEE Trans. Vis. Comput. Graph. 25(1): 1193-1203 (2019) - [c65]Sam Ade Jacobs, Jim Gaffney, Tom Benson, Peter B. Robinson, J. Luc Peterson, Brian K. Spears, Brian Van Essen, David Hysom, Jae-Seung Yeom, Tim Moon, Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer:
Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CLUSTER 2019: 1-10 - [c64]Jayaraman J. Thiagarajan, Irene Kim, Rushil Anirudh, Peer-Timo Bremer:
Understanding Deep Neural Networks through Input Uncertainties. ICASSP 2019: 2812-2816 - [c63]Jayaraman J. Thiagarajan, Rushil Anirudh, Rahul Sridhar, Peer-Timo Bremer:
Unsupervised Dimension Selection Using a Blue Noise Graph Spectrum. ICASSP 2019: 5436-5440 - [c62]Francesco Di Natale, Harsh Bhatia, Timothy S. Carpenter, Chris Neale, Sara Kokkila Schumacher, Tomas Oppelstrup, Liam Stanton, Xiaohua Zhang, Shiv Sundram, Thomas R. W. Scogland, Gautham Dharuman, Michael P. Surh, Yue Yang, Claudia Misale, Lars Schneidenbach, Carlos H. A. Costa, Changhoan Kim, Bruce D'Amora, Sandrasegaram Gnanakaran, Dwight V. Nissley, Frederick H. Streitz, Felice C. Lightstone, Peer-Timo Bremer, James N. Glosli, Helgi I. Ingólfsson:
A massively parallel infrastructure for adaptive multiscale simulations: modeling RAS initiation pathway for cancer. SC 2019: 57:1-57:16 - [i21]Bhavya Kailkhura, Jayaraman J. Thiagarajan, Qunwei Li, Peer-Timo Bremer:
A Look at the Effect of Sample Design on Generalization through the Lens of Spectral Analysis. CoRR abs/1906.02732 (2019) - [i20]Shusen Liu, Di Wang, Dan Maljovec, Rushil Anirudh, Jayaraman J. Thiagarajan, Sam Ade Jacobs, Brian C. Van Essen, David Hysom, Jae-Seung Yeom, Jim Gaffney, J. Luc Peterson, Peter B. Robinson, Harsh Bhatia, Valerio Pascucci, Brian K. Spears, Peer-Timo Bremer:
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications. CoRR abs/1907.08325 (2019) - [i19]Jayaraman J. Thiagarajan, Bindya Venkatesh, Prasanna Sattigeri, Peer-Timo Bremer:
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors. CoRR abs/1909.04079 (2019) - [i18]Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer:
Function Preserving Projection for Scalable Exploration of High-Dimensional Data. CoRR abs/1909.11804 (2019) - [i17]Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer, Brian K. Spears:
Exploring Generative Physics Models with Scientific Priors in Inertial Confinement Fusion. CoRR abs/1910.01666 (2019) - [i16]Sam Ade Jacobs, Brian Van Essen, David Hysom, Jae-Seung Yeom, Tim Moon, Rushil Anirudh, Jayaraman J. Thiagarajan, Shusen Liu, Peer-Timo Bremer, Jim Gaffney, Tom Benson, Peter B. Robinson, J. Luc Peterson, Brian K. Spears:
Parallelizing Training of Deep Generative Models on Massive Scientific Datasets. CoRR abs/1910.02270 (2019) - [i15]J. Luc Peterson, Rushil Anirudh, Kevin Athey, Benjamin Bay, Peer-Timo Bremer, Vic Castillo, Francesco Di Natale, David Fox, Jim A. Gaffney, David Hysom, Sam Ade Jacobs, Bhavya Kailkhura, Joe Koning, Bogdan Kustowski, Steven H. Langer, Peter B. Robinson, Jessica Semler, Brian K. Spears, Jayaraman J. Thiagarajan, Brian Van Essen, Jae-Seung Yeom:
Merlin: Enabling Machine Learning-Ready HPC Ensembles. CoRR abs/1912.02892 (2019) - [i14]Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Timo Bremer:
MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking. CoRR abs/1912.07748 (2019) - [i13]Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Brian K. Spears:
Improved Surrogates in Inertial Confinement Fusion with Manifold and Cycle Consistencies. CoRR abs/1912.08113 (2019) - [i12]Enrico Bertini, Peer-Timo Bremer, Daniela Oelke, Jayaraman J. Thiagarajan:
Machine Learning Meets Visualization to Make Artificial Intelligence Interpretable (Dagstuhl Seminar 19452). Dagstuhl Reports 9(11): 24-33 (2019) - 2018
- [j52]Jayaraman J. Thiagarajan, Shusen Liu, Karthikeyan Natesan Ramamurthy, Peer-Timo Bremer:
Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections. Comput. Graph. Forum 37(3): 241-251 (2018) - [j51]Gordon L. Kindlmann, Charisee Chiw, T. Huynh, Attila Gyulassy, John H. Reppy, Peer-Timo Bremer:
Rendering and Extracting Extremal Features in 3D Fields. Comput. Graph. Forum 37(3): 525-536 (2018) - [j50]Harsh Bhatia, Nikhil Jain, Abhinav Bhatele, Yarden Livnat, Jens Domke, Valerio Pascucci, Peer-Timo Bremer:
Interactive Investigation of Traffic Congestion on Fat-Tree Networks Using TreeScope. Comput. Graph. Forum 37(3): 561-572 (2018) - [j49]Harsh Bhatia, Attila Gyulassy, Vincenzo Lordi, John E. Pask, Valerio Pascucci, Peer-Timo Bremer:
TopoMS: Comprehensive topological exploration for molecular and condensed-matter systems. J. Comput. Chem. 39(16): 936-952 (2018) - [j48]Bhavya Kailkhura, Jayaraman J. Thiagarajan, Charvi Rastogi, Pramod K. Varshney, Peer-Timo Bremer:
A Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms. J. Mach. Learn. Res. 19: 34:1-34:46 (2018) - [j47]Shusen Liu, Peer-Timo Bremer, Jayaraman J. Thiagarajan, Vivek Srikumar, Bei Wang, Yarden Livnat, Valerio Pascucci:
Visual Exploration of Semantic Relationships in Neural Word Embeddings. IEEE Trans. Vis. Comput. Graph. 24(1): 553-562 (2018) - [j46]Will Usher, Pavol Klacansky, Frederick Federer, Peer-Timo Bremer, Aaron Knoll, Jeff Yarch, Alessandra Angelucci, Valerio Pascucci:
A Virtual Reality Visualization Tool for Neuron Tracing. IEEE Trans. Vis. Comput. Graph. 24(1): 994-1003 (2018) - [j45]Alfredo Giménez, Todd Gamblin, Ilir Jusufi, Abhinav Bhatele, Martin Schulz, Peer-Timo Bremer, Bernd Hamann:
MemAxes: Visualization and Analytics for Characterizing Complex Memory Performance Behaviors. IEEE Trans. Vis. Comput. Graph. 24(7): 2180-2193 (2018) - [c61]Rushil Anirudh, Hyojin Kim, Jayaraman J. Thiagarajan, K. Aditya Mohan, Kyle Champley, Timo Bremer:
Lose the Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion. CVPR 2018: 6343-6352 - [c60]Shusen Liu, Tao Li, Zhimin Li, Vivek Srikumar, Valerio Pascucci, Peer-Timo Bremer:
Visual Interrogation of Attention-Based Models for Natural Language Inference and Machine Comprehension. EMNLP (Demonstration) 2018: 36-41 - [c59]Steve Petruzza, Sean Treichler, Valerio Pascucci, Peer-Timo Bremer:
BabelFlow: An Embedded Domain Specific Language for Parallel Analysis and Visualization. IPDPS 2018: 463-473 - [i11]Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Timo Bremer:
An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks. CoRR abs/1805.07281 (2018) - [i10]Gowtham Muniraju, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Peer-Timo Bremer:
Controlled Random Search Improves Sample Mining and Hyper-Parameter Optimization. CoRR abs/1809.01712 (2018) - [i9]Jayaraman J. Thiagarajan, Irene Kim, Rushil Anirudh, Peer-Timo Bremer:
Understanding Deep Neural Networks through Input Uncertainties. CoRR abs/1810.13425 (2018) - [i8]Jayaraman J. Thiagarajan, Rushil Anirudh, Rahul Sridhar, Peer-Timo Bremer:
Unsupervised Dimension Selection using a Blue Noise Spectrum. CoRR abs/1810.13427 (2018) - [i7]Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura, Timo Bremer:
MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense. CoRR abs/1811.08484 (2018) - 2017
- [j44]Shusen Liu, Dan Maljovec, Bei Wang, Peer-Timo Bremer, Valerio Pascucci:
Visualizing High-Dimensional Data: Advances in the Past Decade. IEEE Trans. Vis. Comput. Graph. 23(3): 1249-1268 (2017) - [j43]Dongmei Niu, Peer-Timo Bremer, Peter Lindstrom, Bernd Hamann, Yuanfeng Zhou, Caiming Zhang:
Two-dimensional shape retrieval using the distribution of extrema of Laplacian eigenfunctions. Vis. Comput. 33(5): 607-624 (2017) - [c58]Wathsala Widanagamaachchi, Yarden Livnat, Peer-Timo Bremer, Scott L. DuVall, Valerio Pascucci:
Interactive Visualization and Exploration of Patient Progression in a Hospital Setting. AMIA 2017 - [c57]Wathsala Widanagamaachchi, Alexander Jacques, Bei Wang, Erik T. Crosman, Peer-Timo Bremer, Valerio Pascucci, John D. Horel:
Exploring the evolution of pressure-perturbations to understand atmospheric phenomena. PacificVis 2017: 101-110 - [c56]Rushil Anirudh, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Peer-Timo Bremer:
Poisson Disk Sampling on the Grassmannnian: Applications in Subspace Optimization. CVPR Workshops 2017: 690-698 - [c55]