4 papers
Learning to Represent Individual Differences for Choice Decision Making
Yan-Ying Chen, Yue Weng, Alexandre Filipowicz +7
Human decision making can be challenging to predict because decisions are affected by a number of complex factors. Adding to this complexity, decision-making processes can differ c…
ConjointNet: Enhancing Conjoint Analysis for Preference Prediction with Representation Learning
Yanxia Zhang, Francine Chen, Shabnam Hakimi +9
Understanding consumer preferences is essential to product design and predicting market response to these new products. Choice-based conjoint analysis is widely used to model user…
Stylish and Functional: Guided Interpolation Subject to Physical Constraints
Yan-Ying Chen, Nikos Arechiga, Chenyang Yuan +3
Generative AI is revolutionizing engineering design practices by enabling rapid prototyping and manipulation of designs. One example of design manipulation involves taking two refe…
Understanding the Cognitive Complexity in Language Elicited by Product Images
Yan-Ying Chen, Shabnam Hakimi, Monica Van +4
Product images (e.g., a phone) can be used to elicit a diverse set of consumer-reported features expressed through language, including surface-level perceptual attributes (e.g., "w…