Search Results for author: Arpan Biswas

Found 3 papers, 2 papers with code

Combining Variational Autoencoders and Physical Bias for Improved Microscopy Data Analysis

1 code implementation8 Feb 2023 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 of structural, physical, and chemical properties of materials.

Optimizing Training Trajectories in Variational Autoencoders via Latent Bayesian Optimization Approach

2 code implementations30 Jun 2022 Arpan Biswas, Rama Vasudevan, Maxim Ziatdinov, Sergei V. Kalinin

Unsupervised and semi-supervised ML methods such as variational autoencoders (VAE) have become widely adopted across multiple areas of physics, chemistry, and materials sciences due to their capability in disentangling representations and ability to find latent manifolds for classification and regression of complex experimental data.

A Nested Weighted Tchebycheff Multi-Objective Bayesian Optimization Approach for Flexibility of Unknown Utopia Estimation in Expensive Black-box Design Problems

no code implementations16 Oct 2021 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 better estimation of the uncertain parameters of the weighted-Tchebycheff expensive black-box multi-objective function.

Model Selection regression

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