Shusen Liu

Publication Activity (10 Years)

Years Active: 2011-2023
Publications (10 Years): 39

Top Topics

Visual Exploration

Dimensional Data

Machine Learning

Generative Model

Top Venues

IEEE Trans. Vis. Comput. Graph.

Comput. Graph. Forum

Sci. China Inf. Sci.

Publications

Ruben Glatt, Shusen Liu
Topological Data Analysis Guided Segment Anything Model Prompt Optimization for Zero-Shot Segmentation in Biological Imaging. CoRR (2023)
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 (2023)
Shusen Liu, Xiaowei He, Wencheng Wang, Enhua Wu
Adapted SIMPLE Algorithm for Incompressible SPH Fluids With a Broad Range Viscosity. IEEE Trans. Vis. Comput. Graph. 28 (9) (2022)
Yuzhe Lu, Shusen Liu, Jayaraman J. Thiagarajan, Wesam Sakla, Rushil Anirudh
On-the-fly Object Detection using StyleGAN with CLIP Guidance. CoRR (2022)
Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer
Sparsity Improves Unsupervised Attribute Discovery in Stylegan. ICASSP (2022)
Zhimin Li, Shusen Liu, Xin Yu, Kailkhura Bhavya, Jie Cao, Diffenderfer James Daniel, Peer-Timo Bremer, Valerio Pascucci
"Understanding Robustness Lottery": A Comparative Visual Analysis of Neural Network Pruning Approaches. CoRR (2022)
Sangwon Jeong, Shusen Liu, Matthew Berger
Interactively Assessing Disentanglement in GANs. Comput. Graph. Forum 41 (3) (2022)
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) (2021)
Zhimin Li, Harshitha Menon, Dan Maljovec, Yarden Livnat, Shusen Liu, Kathryn 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) (2021)
Donald Loveland, Shusen Liu, Bhavya Kailkhura, Anna M. Hiszpanski, Yong Han
Reliable Graph Neural Network Explanations Through Adversarial Training. CoRR (2021)
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 (2020)
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) (2020)
Yue Chang, Shusen Liu, Xiaowei He, Sheng Li, Guoping Wang
Semi-analytical Solid Boundary Conditions for Free Surface Flows. Comput. Graph. Forum 39 (7) (2020)
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) (2020)
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) (2020)
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 (2020)
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 (2019)
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) (2019)
Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer
Function Preserving Projection for Scalable Exploration of High-Dimensional Data. CoRR (2019)
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)
Kan He, Shusen Liu, Jinchuan Hou
Separation and approximate separation of multipartite quantum gates. CoRR (2019)
Shusen Liu, Bhavya Kailkhura, Donald Loveland, Yong Han
Generative Counterfactual Introspection for Explainable Deep Learning. GlobalSIP (2019)
Shusen Liu, Bhavya Kailkhura, Donald Loveland, Yong Han
Generative Counterfactual Introspection for Explainable Deep Learning. CoRR (2019)
Shusen Liu, Kan He, Runyao Duan
Implementing termination analysis on quantum programming. Sci. China Inf. Sci. 62 (12) (2019)
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 (2019)
Shusen Liu, Yinan Li, Runyao Duan
Distinguishing unitary gates on the IBM quantum processor. Sci. China Inf. Sci. 62 (7) (2019)
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 (2019)
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) (2018)
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)
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) (2018)
Shusen Liu, Xin Wang, Li Zhou, Ji Guan, Yinan Li, Yang He, Runyao Duan, Mingsheng Ying
Q|SI〉: A Quantum Programming Environment. CoRR (2017)
Shusen Liu, Yang He, Cai Zhang
Towards Automatically Construct Quantum Circuits for Quantum Programs with Quantum Control. VTC Spring (2017)
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) (2017)
Jayaraman J. Thiagarajan, Shusen Liu, Karthikeyan Natesan Ramamurthy, Peer-Timo Bremer
Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections. CoRR (2017)
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) (2016)
Dan Maljovec, Shusen Liu, Bei Wang, Diego Mandelli, Peer-Timo Bremer, Valerio Pascucci, Curtis Smith
Analyzing simulation-based PRA data through traditional and topological clustering: A BWR station blackout case study. Reliab. Eng. Syst. Saf. 145 (2016)
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)
Shusen Liu, Dan Maljovec, Bei Wang, Peer-Timo Bremer, Valerio Pascucci
Visualizing High-Dimensional Data: Advances in the Past Decade. EuroVis (STARs) (2015)
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) (2015)
Shusen Liu, Bei Wang, Peer-Timo Bremer, Valerio Pascucci
Distortion-Guided Structure-Driven Interactive Exploration of High-Dimensional Data. Comput. Graph. Forum 33 (3) (2014)
Shusen Liu, Bei Wang, Jayaraman J. Thiagarajan, Peer-Timo Bremer, Valerio Pascucci
Multivariate volume visualization through dynamic projections. LDAV (2014)
Taifeng Wang, Jiang Bian, Shusen Liu, Yuyu Zhang, Tie-Yan Liu
Psychological advertising: exploring user psychology for click prediction in sponsored search. KDD (2013)
Sen Zhao, Zhifeng Hao, Shusen Liu, Weidi Xu, Han Huang
Multi-objective Evolutionary Algorithm Based on Layer Strategy. ICSI (1) (2012)
Hao Liu, Han Huang, Shusen Liu
Explore Influence of Differential Operator in DE Mutation with Unrestrained Method to Generate Mutant Vector. ICAISC (SIDE-EC) (2012)
Shusen Liu, Joshua A. Levine, Peer-Timo Bremer, Valerio Pascucci
Gaussian mixture model based volume visualization. LDAV (2012)
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) (2011)
Andre Vincent Pascal Grosset, Peihong Zhu, Shusen Liu, Suresh Venkatasubramanian, Mary W. Hall
Evaluating graph coloring on GPUs. PPOPP (2011)