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ORCIDShusen Liu 0001
Person information
- affiliation: Lawrence Livermore National Laboratory, Livermore, CA, USA
- affiliation (PhD 2017): University of Utah, USA
Other persons with the same name
- Shusen Liu — disambiguation page
- Shusen Liu 0002 — University of Technology Sydney, Australia
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2020 – today
- 2024
[j18]Mingwei Li
, Sangwon Jeong, Shusen Liu, Matthew Berger:
CAN: Concept-Aligned Neurons for Visual Comparison of Deep Neural Network Models. Comput. Graph. Forum 43(3) (2024)- [j17]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) - [j16]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) - [c14]Gabriel Perin, Xuxi Chen, Shusen Liu, Bhavya Kailkhura, Zhangyang Wang, Brian Gallagher:
RankMean: Module-Level Importance Score for Merging Fine-tuned LLM Models. ACL (Findings) 2024: 1776-1782 - [c13]Matthew Berger, Shusen Liu:
The Visualization JUDGE: Can Multimodal Foundation Models Guide Visualization Design Through Visual Perception? BELIV 2024: 60-70 - [c12]Sangwon Jeong, Jixian Li, Chris R. Johnson, Shusen Liu, Matthew Berger:
Text-based transfer function design for semantic volume rendering. IEEE VIS 2024: 196-200 - [i20]Sangwon Jeong, Jixian Li, Christopher Johnson, Shusen Liu, Matthew Berger:
Text-based Transfer Function Design for Semantic Volume Rendering. CoRR abs/2406.15634 (2024) - [i19]Sangwon Jeong, Mingwei Li, Matthew Berger, Shusen Liu:
Concept Lens: Visually Analyzing the Consistency of Semantic Manipulation in GANs. CoRR abs/2406.19987 (2024) - [i18]Hongjun Choi, Jayaraman J. Thiagarajan, Ruben Glatt, Shusen Liu:
Enhancing Accuracy and Parameter-Efficiency of Neural Representations for Network Parameterization. CoRR abs/2407.00356 (2024) - [i17]Zhimin Li, Haichao Miao, Valerio Pascucci, Shusen Liu:
Visualization Literacy of Multimodal Large Language Models: A Comparative Study. CoRR abs/2407.10996 (2024) - [i16]Matthew Berger, Shusen Liu:
The Visualization JUDGE : Can Multimodal Foundation Models Guide Visualization Design Through Visual Perception? CoRR abs/2410.04280 (2024) - 2023
- [c11]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 - [c10]Sangwon Jeong, Mingwei Li, Matthew Berger, Shusen Liu:
Concept Lens: Visually Analyzing the Consistency of Semantic Manipulation in GANs. IEEE VIS (Short Papers) 2023: 221-225 - [i15]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) - [i14]Zhimin Li, Shusen Liu, Bhavya Kailkhura, Timo Bremer, Valerio Pascucci:
Instance-wise Linearization of Neural Network for Model Interpretation. CoRR abs/2310.16295 (2023) - [i13]Matthew L. Olson, Shusen Liu, Jayaraman J. Thiagarajan, Bogdan Kustowski, Weng-Keen Wong, Rushil Anirudh:
Transformer-Powered Surrogates Close the ICF Simulation-Experiment Gap with Extremely Limited Data. CoRR abs/2312.03642 (2023) - [i12]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) - 2022
- [j15]Sangwon Jeong, Shusen Liu, Matthew Berger:
Interactively Assessing Disentanglement in GANs. Comput. Graph. Forum 41(3): 85-95 (2022) - [c9]Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer:
Sparsity Improves Unsupervised Attribute Discovery in Stylegan. ICASSP 2022: 3388-3392 - [i11]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) - [i10]Yuzhe Lu, Shusen Liu, Jayaraman J. Thiagarajan, Wesam Sakla, Rushil Anirudh:
On-the-fly Object Detection using StyleGAN with CLIP Guidance. CoRR abs/2210.16742 (2022) - 2021
- [j14]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) - [j13]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) - [i9]Donald Loveland, Shusen Liu, Bhavya Kailkhura, Anna M. Hiszpanski, Yong Han:
Reliable Graph Neural Network Explanations Through Adversarial Training. CoRR abs/2106.13427 (2021) - 2020
- [j12]Anna M. Hiszpanski, Brian Gallagher, Karthik Chellappan, Peggy Li, Shusen Liu, Hyojin Kim, Jinkyu Han, Bhavya Kailkhura, David J. Buttler, Thomas Yong-Jin Han:
Nanomaterial Synthesis Insights from Machine Learning of Scientific Articles by Extracting, Structuring, and Visualizing Knowledge. J. Chem. Inf. Model. 60(6): 2876-2887 (2020) - [j11]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) - [j10]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) - [i8]Shusen Liu, Bhavya Kailkhura, Jize Zhang, Anna M. Hiszpanski, Emily Robertson, Donald Loveland, Thomas Yong-Jin Han:
Actionable Attribution Maps for Scientific Machine Learning. CoRR abs/2006.16533 (2020) - [i7]Shusen Liu, Bhavya Kailkhura, Jize Zhang, Anna M. Hiszpanski, Emily Robertson, Donald Loveland, Thomas Yong-Jin Han:
Explainable Deep Learning for Uncovering Actionable Scientific Insights for Materials Discovery and Design. CoRR abs/2007.08631 (2020)
2010 – 2019
- 2019
- [j9]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) - [c8]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 - [c7]Shusen Liu, Bhavya Kailkhura, Donald Loveland, Yong Han:
Generative Counterfactual Introspection for Explainable Deep Learning. GlobalSIP 2019: 1-5 - [i6]Shusen Liu, Bhavya Kailkhura, Donald Loveland, Yong Han:
Generative Counterfactual Introspection for Explainable Deep Learning. CoRR abs/1907.03077 (2019) - [i5]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) - [i4]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) - [i3]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) - [i2]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) - 2018
- [j8]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) - [j7]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) - [c6]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 - 2017
- [b1]Shusen Liu:
Visual Exploration of High-Dimensional Spaces Through Identification, Summarization, and Interpretation of Two-Dimensional Projections. University of Utah, USA, 2017 - [j6]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) - [i1]Jayaraman J. Thiagarajan, Shusen Liu, Karthikeyan Natesan Ramamurthy, Peer-Timo Bremer:
Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections. CoRR abs/1712.07106 (2017) - 2016
- [j5]Shusen Liu, Peer-Timo Bremer, J. J. Jayaraman, Bei Wang, Brian Summa, Valerio Pascucci:
The Grassmannian Atlas: A General Framework for Exploring Linear Projections of High-Dimensional Data. Comput. Graph. Forum 35(3): 1-10 (2016) - [j4]Dan Maljovec, Shusen Liu, Bei Wang, Diego Mandelli, Peer-Timo Bremer, Valerio Pascucci, Curtis L. Smith:
Analyzing simulation-based PRA data through traditional and topological clustering: A BWR station blackout case study. Reliab. Eng. Syst. Saf. 145: 262-276 (2016) - [c5]Cameron Christensen, Ji-Woo Lee, Shusen Liu, Peer-Timo Bremer, Giorgio Scorzelli, Valerio Pascucci:
Embedded domain-specific language and runtime system for progressive spatiotemporal data analysis and visualization. LDAV 2016: 1-10 - 2015
- [j3]Shusen Liu, Bei Wang, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Valerio Pascucci:
Visual Exploration of High-Dimensional Data through Subspace Analysis and Dynamic Projections. Comput. Graph. Forum 34(3): 271-280 (2015) - [c4]Shusen Liu, Dan Maljovec, Bei Wang, Peer-Timo Bremer, Valerio Pascucci:
Visualizing High-Dimensional Data: Advances in the Past Decade. EuroVis (STARs) 2015: 127-147 - 2014
- [j2]Shusen Liu, Bei Wang, Peer-Timo Bremer, Valerio Pascucci:
Distortion-Guided Structure-Driven Interactive Exploration of High-Dimensional Data. Comput. Graph. Forum 33(3): 101-110 (2014) - [c3]Shusen Liu, Bei Wang, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Valerio Pascucci:
Multivariate volume visualization through dynamic projections. LDAV 2014: 35-42 - 2012
- [c2]Shusen Liu, Joshua A. Levine, Peer-Timo Bremer, Valerio Pascucci:
Gaussian mixture model based volume visualization. LDAV 2012: 73-77 - 2011
- [j1]Janine Bennett, Vaidyanathan Krishnamoorthy, Shusen Liu, Ray W. Grout, Evatt R. Hawkes, Jacqueline H. Chen, Jason Shepherd, Valerio Pascucci, Peer-Timo Bremer:
Feature-Based Statistical Analysis of Combustion Simulation Data. IEEE Trans. Vis. Comput. Graph. 17(12): 1822-1831 (2011) - [c1]Andre Vincent Pascal Grosset, Peihong Zhu, Shusen Liu, Suresh Venkatasubramanian, Mary W. Hall:
Evaluating graph coloring on GPUs. PPoPP 2011: 297-298
Coauthor Index
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