Prediction of processing maps for transient liquid phase diffusion bonding of Cu/Sn/Cu joints in microelectronics packaging. - M. S. Park; S. L. Gibbons; Raymundo Arróyave (Microelectron. Reliab., 2014)

Fast Exact Computation of Expected HyperVolume Improvement. - Guang Zhao; Raymundo Arróyave; Xiaoning Qian (CoRR, 2018)

Numerical and experimental analysis of heat distribution in the laser powder bed fusion of Ti-6Al-4V. - Kubra Karayagiz; Alaa Elwany; Gustavo Tapia; Brian Franco; Luke Johnson; Ji Ma; Ibrahim Karaman; Raymundo Arróyave (IISE Trans., 2019)

Deep Multimodal Transfer-Learned Regression in Data-Poor Domains. - Levi D. McClenny; Mulugeta A. Haile; Vahid Attari; Brian M. Sadler; Ulisses M. Braga-Neto; Raymundo Arróyave (CoRR, 2020)

Physics-constrained Automatic Feature Engineering for Predictive Modeling in Materials Science. - Ziyu Xiang; Mingzhou Fan; Guillermo Vázquez Tovar; William Trehern; Byung-Jun Yoon; Xiaofeng Qian; Raymundo Arróyave; Xiaoning Qian (AAAI, 2021)

Efficient Propagation of Uncertainty via Reordering Monte Carlo Samples. - Danial Khatamsaz; Vahid Attari; Raymundo Arróyave; Douglas L. Allaire (CoRR, 2023)

Deep learning-accelerated computational framework based on Physics Informed Neural Network for the solution of linear elasticity. - Arunabha M. Roy; Rikhi Bose; Veera Sundararaghavan; Raymundo Arróyave (Neural Networks, 2023)

Knowledge-driven learning, optimization, and experimental design under uncertainty for materials discovery. - Xiaoning Qian; Byung-Jun Yoon; Raymundo Arróyave; Xiaofeng Qian; Edward R. Dougherty (Patterns, 2023)

Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation. - Keqiang Yan; Xiner Li; Hongyi Ling; Kenna Ashen; Carl Edwards; Raymundo Arróyave; Marinka Zitnik; Heng Ji 001; Xiaofeng Qian; Xiaoning Qian; Shuiwang Ji (NeurIPS, 2024)

Multi-fidelity Bayesian Optimization with Multiple Information Sources of Input-dependent Fidelity. - Mingzhou Fan; Byung-Jun Yoon; Edward R. Dougherty; Nathan M. Urban; Francis J. Alexander; Raymundo Arróyave; Xiaoning Qian (UAI, 2024)

Label Propagation Training Schemes for Physics-Informed Neural Networks and Gaussian Processes. - Ming Zhong 008; Dehao Liu; Raymundo Arróyave; Ulisses Braga-Neto (CoRR, 2024)

Supply Risk-Aware Alloy Discovery and Design. - Mrinalini Mulukutla; Robert Robinson; Danial Khatamsaz; Brent Vela; Nhu Vu; Raymundo Arróyave (CoRR, 2024)

Accelerating CALPHAD-based Phase Diagram Predictions in Complex Alloys Using Universal Machine Learning Potentials: Opportunities and Challenges. - Siya Zhu; Raymundo Arróyave; Doguhan Saritürk (CoRR, 2024)

Towards Autonomous Experimentation: Bayesian Optimization over Problem Formulation Space for Accelerated Alloy Development. - Danial Khatamsaz; Joseph Wagner; Brent Vela; Raymundo Arróyave; Douglas L. Allaire (CoRR, 2025)

Physics-Informed Gaussian Process Classification for Constraint-Aware Alloy Design. - Christofer Hardcastle; Ryan O. Mullan; Raymundo Arróyave; Brent Vela (CoRR, 2025)

A Materials Foundation Model via Hybrid Invariant-Equivariant Architectures. - Keqiang Yan; Montgomery Bohde; Andrii Kryvenko; Ziyu Xiang; Kaiji Zhao; Siya Zhu; Saagar Kolachina; Doguhan Saritürk; Jianwen Xie; Raymundo Arróyave; Xiaoning Qian; Xiaofeng Qian; et al. (CoRR, 2025)

Toward Greater Autonomy in Materials Discovery Agents: Unifying Planning, Physics, and Scientists. - Lianhao Zhou; Hongyi Ling; Keqiang Yan; Kaiji Zhao; Xiaoning Qian; Raymundo Arróyave; Xiaofeng Qian; Shuiwang Ji (CoRR, 2025)

Accurate and Uncertainty-Aware Multi-Task Prediction of HEA Properties Using Prior-Guided Deep Gaussian Processes. - Sk Md Ahnaf Akif Alvi; Mrinalini Mulukutla; Nicolas Flores; Danial Khatamsaz; Jan Janssen; Danny Perez; Douglas L. Allaire; Vahid Attari; Raymundo Arróyave (CoRR, 2025)