activity
20182021
most citedBayesian Optimization for Materials Design with Mixed Quantitative and Qualitative Variables

9 citations · 14 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL20211 cited

Interpretable and Low-Resource Entity Matching via Decoupling Feature Learning from Decision Making

Zijun Yao, Chengjiang Li, Tiansi Dong +6

Entity Matching (EM) aims at recognizing entity records that denote the same real-world object. Neural EM models learn vector representation of entity descriptions and match entiti…

stat.ML20199 cited

Bayesian Optimization for Materials Design with Mixed Quantitative and Qualitative Variables

Yichi Zhang, Daniel Apley, Wei Chen

Although Bayesian Optimization (BO) has been employed for accelerating materials design in computational materials engineering, existing works are restricted to problems with quant…

physics.app-ph2019

Designing Anisotropic Microstructures with Spectral Density Function

Akshay Iyer, Rabindra Dulal, Yichi Zhang +4

Materials' microstructure strongly influences its performance and is thus a critical aspect in design of functional materials. Previous efforts on microstructure mediated design mo…

physics.comp-ph20194 cited

Data-Centric Mixed-Variable Bayesian Optimization For Materials Design

Akshay Iyer, Yichi Zhang, Aditya Prasad +5

Materials design can be cast as an optimization problem with the goal of achieving desired properties, by varying material composition, microstructure morphology, and processing co…

stat.ML2018

A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors

Yichi Zhang, Siyu Tao, Wei Chen +1

Computer simulations often involve both qualitative and numerical inputs. Existing Gaussian process (GP) methods for handling this mainly assume a different response surface for ea…