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20232026
most citedRoadmap on Atomic-scale Semiconductor Devices

20 citations · 55 across the 25 of their papers we have counts for

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Showing 2025Show all

8 papers · 1 filter

cs.LG2025

DIVIDE: A Framework for Learning from Independent Multi-Mechanism Data Using Deep Encoders and Gaussian Processes

Vivek Chawla, Boris Slautin, Utkarsh Pratiush +2

Scientific datasets often arise from multiple independent mechanisms such as spatial, categorical or structural effects, whose combined influence obscures their individual contribu…

cs.CV2025

SAM: Task-Adaptive SAM with Physics-Guided Rewards

Kamyar Barakati, Utkarsh Pratiush, Sheryl L. Sanchez +5

Image segmentation is a critical task in microscopy, essential for accurately analyzing and interpreting complex visual data. This task can be performed using custom models trained…

cond-mat.mtrl-sci2025

Attention-Based Explainability for Structure-Property Relationships

Boris N. Slautin, Utkarsh Pratiush, Yongtao Liu +4

Machine learning methods are emerging as a universal paradigm for constructing correlative structure-property relationships in materials science based on multimodal characterizatio…

cond-mat.mtrl-sci2025★ 1 cited

Mic-hackathon 2024: Hackathon on Machine Learning for Electron and Scanning Probe Microscopy

Utkarsh Pratiush, Austin Houston, Kamyar Barakati +70

Microscopy is a primary source of information on materials structure and functionality at nanometer and atomic scales. The data generated is often well-structured, enriched with me…

cond-mat.mtrl-sci2025

Domain Switching on the Pareto Front: Multi-Objective Deep Kernel Learning in Automated Piezoresponse Force Microscopy

Yu Liu, Utkarsh Pratiush, Kamyar Barakati +5

Ferroelectric polarization switching underpins the functional performance of a wide range of materials and devices, yet its dependence on complex local microstructural features ren…

cs.LG2025

Integrating Predictive and Generative Capabilities by Latent Space Design via the DKL-VAE Model

Boris N. Slautin, Utkarsh Pratiush, Doru C. Lupascu +2

We introduce a Deep Kernel Learning Variational Autoencoder (VAE-DKL) framework that integrates the generative power of a Variational Autoencoder (VAE) with the predictive nature o…

eess.IV2025

Rewards-based image analysis in microscopy

Kamyar Barakati, Yu Liu, Utkarsh Pratiush +2

Imaging and hyperspectral data analysis is central to progress across biology, medicine, chemistry, and physics. The core challenge lies in converting high-resolution or high-dimen…

quant-ph2025★ 20 cited

Roadmap on Atomic-scale Semiconductor Devices

Steven R. Schofield, Andrew J. Fisher, Eran Ginossar +47

Spin states in semiconductors provide exceptionally stable and noise-resistant environments for qubits, positioning them as optimal candidates for reliable quantum computing techno…