Neural networks attract significant attention in almost every field due to their widespread applications in various tasks. However, developers often struggle with debugging due to the black-box nature of neural networks. Visual analytics provides an intuitive way for developers to understand the hidden states and underlying complex transformations in neural networks. Existing visual analytics tools for neural networks have been demonstrated to be effective in providing useful hints for debugging certain network architectures. However, these approaches are often architecture-specific with strong assumptions of how the network should be understood. This limits their use when the network architecture or the exploration goal changes. In this paper, we present a general model and a programming toolkit, Neural Network Visualization Builder (NNVisBuilder), for prototyping visual analytics systems to understand neural networks. NNVisBuilder covers the common data transformation and interaction model involved in existing tools for exploring neural networks. It enables developers to customize a visual analytics interface for answering their specific questions about networks. NNVisBuilder is compatible with PyTorch so that developers can integrate the visualization code into their learning code seamlessly. We demonstrate the applicability by reproducing several existing visual analytics systems for networks with NNVisBuilder. The source code and some example cases can be found at https://github.com/sysuvis/NVB.

Cultural relics visualization brings digital archives of relics to broader audiences in many applications, such as education, historical research, and virtual museums. However, previous research mainly focused on modeling and rendering the relics. While enhancing accessibility, these techniques still provide limited ability to improve user engagement. In this paper, we introduce RelicCARD, a semantics-based augmented reality (AR) tangible interaction design for exploring cultural relics. Our design uses an easily available tangible interface to encourage the users to interact with a large collection of relics. The tangible interface allows users to explore, select, and arrange relics to form customized scenes. To guide the design of the interface, we formalize a design space by connecting the semantics in relics, the tangible interaction patterns, and the exploration tasks. We realize the design space as a tangible interactive prototype and examine its feasibility and effectiveness using multiple case studies and an expert evaluation. Finally, we discuss the findings in the evaluation and future directions to improve the design and implementation of the interactive design space.