6 citations · 10 across the 5 of their papers we have counts for
5 papers
A dynamic Bayesian optimized active recommender system for curiosity-driven Human-in-the-loop automated experiments
Arpan Biswas, Yongtao Liu, Nicole Creange +6
Optimization of experimental materials synthesis and characterization through active learning methods has been growing over the last decade, with examples ranging from measurements…
Combining Variational Autoencoders and Physical Bias for Improved Microscopy Data Analysis
Arpan Biswas, Maxim Ziatdinov, Sergei V. Kalinin
Electron and scanning probe microscopy produce vast amounts of data in the form of images or hyperspectral data, such as EELS or 4D STEM, that contain information on a wide range o…
Optimizing Training Trajectories in Variational Autoencoders via Latent Bayesian Optimization Approach
Arpan Biswas, Rama Vasudevan, Maxim Ziatdinov +1
Unsupervised and semi-supervised ML methods such as variational autoencoders (VAE) have become widely adopted across multiple areas of physics, chemistry, and materials sciences du…
A Nested Weighted Tchebycheff Multi-Objective Bayesian Optimization Approach for Flexibility of Unknown Utopia Estimation in Expensive Black-box Design Problems
Arpan Biswas, Claudio Fuentes, Christopher Hoyle
We propose a nested weighted Tchebycheff Multi-objective Bayesian optimization framework where we build a regression model selection procedure from an ensemble of models, towards b…
Multi-objective Bayesian optimization of ferroelectric materials with interfacial control for memory and energy storage applications
Arpan Biswas, Anna N. Morozovska, Maxim Ziatdinov +2
Optimization of materials performance for specific applications often requires balancing multiple aspects of materials functionality. Even for the cases where generative physical m…