Jiaxin Zhang

According to our database, Jiaxin Zhang authored at least 24 papers between 2016 and 2024.

Collaborative distances:

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

2024

On the Quantification of Image Reconstruction Uncertainty without Training Data.

Jiaxin Zhang, Sirui Bi, Victor Fung

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023

RecUP-FL: Reconciling Utility and Privacy in Federated learning via User-configurable Privacy Defense.

Yue Cui, Syed Irfan Ali Meerza, Zhuohang Li, Luyang Liu, Jiaxin Zhang, Jian Liu

Proceedings of the 2023 ACM Asia Conference on Computer and Communications Security, 2023

AutoNF: Automated Architecture Optimization of Normalizing Flows with Unconstrained Continuous Relaxation Admitting Optimal Discrete Solution.

Yu Wang, Ján Drgona, Jiaxin Zhang, Karthik Somayaji Nanjangud Suryanarayana, Malachi Schram, Frank Liu, Peng Li

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Accelerating Inverse Learning via Intelligent Localization with Exploratory Sampling.

Sirui Bi, Victor Fung, Jiaxin Zhang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Atomic structure generation from reconstructing structural fingerprints.

Victor Fung, Shuyi Jia, Jiaxin Zhang, Sirui Bi, Junqi Yin, Panchapakesan Ganesh

Mach. Learn. Sci. Technol., December, 2022

Fair and Privacy-Preserving Alzheimer's Disease Diagnosis Based on Spontaneous Speech Analysis via Federated Learning.

Syed Irfan Ali Meerza, Zhuohang Li, Luyang Liu, Jiaxin Zhang, Jian Liu

Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Privacy-preserving Speech-based Depression Diagnosis via Federated Learning.

Yue Cui, Zhuohang Li, Luyang Liu, Jiaxin Zhang, Jian Liu

Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage.

Zhuohang Li, Jiaxin Zhang, Luyang Liu, Jian Liu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Gradient-Based Novelty Detection Boosted by Self-Supervised Binary Classification.

Jingbo Sun, Li Yang, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar, Deliang Fan, Yu Cao

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Simulation Intelligence: Towards a New Generation of Scientific Methods.

Alexander Lavin, Hector Zenil, Brooks Paige, David Krakauer, Justin Gottschlich, Tim Mattson, Anima Anandkumar, Sanjay Choudry, Kamil Rocki, Atilim Günes Baydin, Carina Prunkl, Olexandr Isayev, Erik Peterson, Peter L. McMahon, Jakob H. Macke, Kyle Cranmer, Jiaxin Zhang, Haruko M. Wainwright, Adi Hanuka, Manuela Veloso, Samuel Assefa, Stephan Zheng, Avi Pfeffer

CoRR, 2021

Inverse design of two-dimensional materials with invertible neural networks.

Victor Fung, Jiaxin Zhang, Guoxiang Hu, Panchapakesan Ganesh, Bobby G. Sumpter

CoRR, 2021

A Hybrid Gradient Method to Designing Bayesian Experiments for Implicit Models.

Jiaxin Zhang, Sirui Bi, Guannan Zhang

CoRR, 2021

Self-supervised Novelty Detection for Continual Learning: A Gradient-Based Approach Boosted by Binary Classification.

Jingbo Sun, Li Yang, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar, Deliang Fan, Yu Cao

Proceedings of the Continual Semi-Supervised Learning - First International Workshop, 2021

Enabling long-range exploration in minimization of multimodal functions.

Jiaxin Zhang, Hoang Tran, Dan Lu, Guannan Zhang

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

On the Stochastic Stability of Deep Markov Models.

Ján Drgona, Sayak Mukherjee, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Byzantine-robust Federated Learning through Spatial-temporal Analysis of Local Model Updates.

Zhuohang Li, Luyang Liu, Jiaxin Zhang, Jian Liu

Proceedings of the 27th IEEE International Conference on Parallel and Distributed Systems, 2021

A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models.

Jiaxin Zhang, Sirui Bi, Guannan Zhang

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

On the quantification and efficient propagation of imprecise probabilities with copula dependence.

Jiaxin Zhang, Michael D. Shields

Int. J. Approx. Reason., 2020

Scalable Deep-Learning-Accelerated Topology Optimization for Additively Manufactured Materials.

Sirui Bi, Jiaxin Zhang, Guannan Zhang

CoRR, 2020

Thermodynamic Consistent Neural Networks for Learning Material Interfacial Mechanics.

Jiaxin Zhang, Congjie Wei, Chenglin Wu

CoRR, 2020

Data Driven Modeling of Interfacial Traction Separation Relations using Thermodynamic Consistent Neural Network (TCNN).

Congjie Wei, Jiaxin Zhang, Kenneth M. Liechti, Chenglin Wu

CoRR, 2020

A Scalable Evolution Strategy with Directional Gaussian Smoothing for Blackbox Optimization.

Jiaxin Zhang, Hoang Tran, Dan Lu, Guannan Zhang

CoRR, 2020

2019

Learning nonlinear level sets for dimensionality reduction in function approximation.

Guannan Zhang, Jiaxin Zhang, Jacob D. Hinkle

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2016

The generalization of Latin hypercube sampling.

Michael D. Shields, Jiaxin Zhang

Reliab. Eng. Syst. Saf., 2016