WizMap: Scalable Interactive Visualization for Exploring Large Machine Learning Embeddings
Paper
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2306.09328
•
Published
Jay Wang
xiaohk
AI & ML interests
My research focuses on making AI more accessible, interpretable, and accountable, by designing and developing novel interactive interfaces for people to easily and enjoyably interact with ML systems at scale.
Organizations
authored
15
papers
about 2 years ago
NOVA: A Practical Method for Creating Notebook-Ready Visual Analytics
Paper
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2205.03963
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Published
SuperNOVA: Design Strategies and Opportunities for Interactive Visualization in Computational Notebooks
Paper
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2305.03039
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Published
Angler: Helping Machine Translation Practitioners Prioritize Model Improvements
Paper
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2304.05967
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Published
WebSHAP: Towards Explaining Any Machine Learning Models Anywhere
Paper
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2303.09545
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Published
GAM Coach: Towards Interactive and User-centered Algorithmic Recourse
Paper
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2302.14165
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Published
Overcoming Language Disparity in Online Content Classification with Multimodal Learning
Paper
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2205.09744
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Published
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1
StickyLand: Breaking the Linear Presentation of Computational Notebooks
Paper
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2202.11086
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Published
GAM Changer: Editing Generalized Additive Models with Interactive Visualization
Paper
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2112.03245
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Published
Dodrio: Exploring Transformer Models with Interactive Visualization
Paper
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2103.14625
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Published
Putting Humans in the Natural Language Processing Loop: A Survey
Paper
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2103.04044
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Published
CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization
Paper
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2004.15004
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Published
CNN 101: Interactive Visual Learning for Convolutional Neural Networks
Paper
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2001.02004
•
Published
Bluff: Interactively Deciphering Adversarial Attacks on Deep Neural Networks
Paper
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2009.02608
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Published
TimberTrek: Exploring and Curating Sparse Decision Trees with Interactive Visualization
Paper
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2209.09227
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Published
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2
authored
a
paper
over 2 years ago