5 papers
Physically Constrained Ensemble Gaussian Process Modelling for Expensive Quantum Systems with Heteroskedastic Noise
Arpan Biswas, Sutirtha Paul, Joseph Agada +2
Accurate modeling of quantum many-body systems often requires computationally expensive simulations such as Density Matrix Renormalization Group (DMRG) or Quantum Monte Carlo (QMC)…
Beyond Scalar Objectives: Expert-Feedback-Driven Autonomous Experimentation for Scientific Discovery at the Nanoscale
Ralph Bulanadi, Jefferey Baxter, Arpan Biswas +5
Self-driving laboratories or autonomous experimentation are emerging as transformative platforms for accelerating scientific discovery. Bayesian optimization (BO) is among the most…
Human-AI Collaborative Autonomous Experimentation With Proxy Modeling for Comparative Observation
Arpan Biswas, Hiroshi Funakubo, Yongtao Liu
Optimization for different tasks like material characterization, synthesis, and functional properties for desired applications over multi-dimensional control parameters need a rapi…
Physically-Constrained Autoencoder-Assisted Bayesian Optimization for Refinement of High-Dimensional Defect-Sensitive Single Crystalline Structure
Joseph Oche Agada, Andrew McAninch, Haley Day +6
Physical properties and functionalities of materials are dictated by global crystal structures as well as local defects. To establish a structure-property relationship, not only th…
Beyond Optimization: Exploring Novelty Discovery in Autonomous Experiments
Ralph Bulanadi, Jawad Chowdhury, Funakubo Hiroshi +4
Autonomous experiments (AEs) are transforming how scientific research is conducted by integrating artificial intelligence with automated experimental platforms. Current AEs primari…