Sergei V. Kalinin

81 papers A 1B 3Misc 1Journal 74Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Autonomous Probe Microscopy with Robust Bag-of-Features Multi-Objective Bayesian Optimization: Pareto-Front Mapping of Nanoscale Structure-Property Trade-Offs. CoRR Kamyar Barakati, Haochen Zhu, C. Charlotte Buchanan, Dustin A. Gilbert, Philip D. Rack, Sergei V. Kalinin
2026	J	`jnl`	Novelty-Driven Target-Space Discovery in Automated Electron and Scanning Probe Microscopy. CoRR Utkarsh Pratiush, Kamyar Barakati, Boris N. Slautin, Catherine C. Bodinger, Christopher D. Lowe, Brandi M. Cossairt, Sergei V. Kalinin
2026	J	`jnl`	Towards Self-Optimizing Electron Microscope: Robust Tuning of Aberration Coefficients via Physics-Aware Multi-Objective Bayesian Optimization. CoRR Utkarsh Pratiush, Austin Houston, Richard Liu, Gerd Duscher, Sergei V. Kalinin
2025	J	`jnl`	AI4X Roadmap: Artificial Intelligence for the advancement of scientific pursuit and its future directions. CoRR Stephen G. Dale, Nikita Kazeev, Alastair J. A. Price, Victor Posligua, Stephan Roche, O. Anatole von Lilienfeld, Konstantin S. Novoselov, Xavier Bresson, Gianmarco Mengaldo, Xudong Chen, Terence J. O'Kane, Emily R. Lines, Matthew J. Allen, Amandine E. Debus, Clayton Miller, Jiayu Zhou, Hiroko H. Dodge, David Rousseau, Andrey Ustyuzhanin, Ziyun Yan, Mario Lanza, Fabio Sciarrino, Ryo Yoshida, Zhidong Leong, Teck Leong Tan, Qianxiao Li, Adil Kabylda, Igor Poltavsky, Alexandre Tkatchenko, Sherif Abdulkader Tawfik, Prathami Divakar Kamath, Théo Jaffrelot Inizan, Kristin A. Persson, Bryant Y. Li, Vir Karan, Chenru Duan, Haojun Jia, Qiyuan Zhao, Hiroyuki Hayashi, Atsuto Seko, Isao Tanaka, Omar M. Yaghi, Tim Gould, Bun Chan, Stefan Vuckovic, Tianbo Li, Min Lin, Zehcen Tang, Yang Li, Yong Xu, Amrita Joshi, Xiaonan Wang, Leonard W. T. Ng, Sergei V. Kalinin, Mahshid Ahmadi, Jiyizhe Zhang, Shuyuan Zhang, Alexei A. Lapkin, Ming Xiao, Zhe Wu, Kedar Hippalgaonkar, Limsoon Wong, Lorenzo Bastonero, Nicola Marzari, Dorye Luis Esteras Cordoba, Andrei Tomut, Alba Quinones Andrade, Jose-Hugo Garcia
2025	J	`jnl`	Causal Discovery from Data Assisted by Large Language Models. CoRR Kamyar Barakati, Alexander Molak, Chris Nelson, Xiaohang Zhang, Ichiro Takeuchi, Sergei V. Kalinin
2025	J	`jnl`	DIVIDE: A Framework for Learning from Independent Multi-Mechanism Data Using Deep Encoders and Gaussian Processes. CoRR Vivek Chawla, Boris N. Slautin, Utkarsh Pratiush, Dayakar Penumadu, Sergei V. Kalinin
2025	J	`jnl`	Design-to-Deployment Continuum Platform for Microscopes and Computing Ecosystems. IEEE Trans. Ind. Informatics Anees Al-Najjar, Nageswara S. V. Rao, Ramanan Sankaran, Debangshu Mukherjee, Kevin Roccapriore, Maxim A. Ziatdinov, Sergei V. Kalinin
2025	J	`jnl`	Domain Switching on the Pareto Front: Multi-Objective Deep Kernel Learning in Automated Piezoresponse Force Microscopy. CoRR Yu Liu, Utkarsh Pratiush, Kamyar Barakati, Hiroshi Funakubo, Ching-Che Lin, Jaegyu Kim, Lane W. Martin, Sergei V. Kalinin
2025	J	`jnl`	Exploring Domain Wall Pinning in Ferroelectrics via Automated High Throughput AFM. CoRR Kamyar Barakati, Yu Liu, Hiroshi Funakubo, Sergei V. Kalinin
2025	J	`jnl`	Integrating Predictive and Generative Capabilities by Latent Space Design via the DKL-VAE Model. CoRR Boris N. Slautin, Utkarsh Pratiush, Doru C. Lupascu, Maxim A. Ziatdinov, Sergei V. Kalinin
2025	J	`jnl`	Mic-hackathon 2024: Hackathon on Machine Learning for Electron and Scanning Probe Microscopy. CoRR Utkarsh Pratiush, Austin Houston, Kamyar Barakati, Aditya Raghavan, Dasol Yoon, Harikrishnan KP, Zhaslan Baraissov, Desheng Ma, Samuel S. Welborn, Mikolaj Jakowski, Shawn-Patrick Barhorst, Alexander J. Pattison, Panayotis Manganaris, Sita Sirisha Madugula, Sai Venkata Gayathri Ayyagari, Vishal Kennedy, Ralph Bulanadi, Michelle Wang, Kieran J. Pang, Ian Addison-Smith, Willy Menacho, Horacio V. Guzman, Alexander Kiefer, Nicholas Furth, Nikola L. Kolev, Mikhail Petrov, Viktoriia Liu, Sergey Ilyev, Srikar Rairao, Tommaso Rodani, Ivan Pinto-Huguet, Xuli Chen, Josep Cruañes, Marta Torrens, Jovan Pomar, Fanzhi Su, Pawan Vedanti, Zhiheng Lyu, Xingzhi Wang, Lehan Yao, Amir Taqieddin, Forrest Laskowski, Xiangyu Yin, Yu-Tsun Shao, Benjamin Fein-Ashley, Yi Jiang, Vineet Kumar, Himanshu Mishra, Yogesh Paul, Adib Bazgir, Rama Chandra Praneeth Madugula, Yuwen Zhang, Pravan Omprakash, Jian Huang, Eric Montufar-Morales, Vivek Chawla, Harshit Sethi, Jie Huang, Lauri Kurki, Grace Guinan, Addison Salvador, Arman H. Ter-Petrosyan, Madeline Van Winkle, Steven R. Spurgeon, Ganesh Narasimha, Zijie Wu, Richard Liu, Yongtao Liu, Boris N. Slautin, Andrew R. Lupini, Rama K. Vasudevan, Gerd Duscher, Sergei V. Kalinin
2025	J	`jnl`	Mic-hackathon 2024: hackathon on machine learning for electron and scanning probe microscopy. Mach. Learn. Sci. Technol. Utkarsh Pratiush, Austin Houston, Kamyar Barakati, Aditya Raghavan, Ralph Bulanadi, Xiangyu Yin, Samuel S. Welborn, Dasol Yoon, Harikrishnan KP, Zhaslan Baraissov, Desheng Ma, Mikolaj Jakowski, Shawn-Patrick Barhorst, Alexander J. Pattison, Panayotis Manganaris, Sita Sirisha Madugula, Sai Venkata Gayathri Ayyagari, Vishal Kennedy, Michelle Wang, Kieran J. Pang, Ian Addison-Smith, Willy Menacho, Horacio V. Guzman, Alexander Kiefer, Nicholas Furth, Nikola L. Kolev, Mikhail Petrov, Viktoriia Liu, Sergey Ilyev, Srikar Rairao, Tommaso Rodani, Ivan Pinto-Huguet, Xuli Chen, Josep Cruañes, Marta Torrens, Jovan Pomar, Fanzhi Su, Pawan Vedanti, Zhiheng Lyu, Xingzhi Wang, Lehan Yao, Amir Taqieddin, Forrest Laskowski, Yu-Tsun Shao, Benjamin Fein-Ashley, Yi Jiang, Vineet Kumar, Himanshu Mishra, Yogesh Paul, Adib Bazgir, Rama Chandra Praneeth Madugula, Yuwen Zhang, Pravan Omprakash, Jian Huang, Eric Montufar-Morales, Vivek Chawla, Harshit Sethi, Jie Huang, Lauri Kurki, Grace Guinan, Addison Salvador, Arman H. Ter-Petrosyan, Madeline Van Winkle, Steven R. Spurgeon, Ganesh Narasimha, Zijie Wu, Richard Liu, Yongtao Liu, Boris N. Slautin, Andrew R. Lupini, Rama K. Vasudevan, Gerd Duscher, Sergei V. Kalinin
2025	J	`jnl`	Reward driven discovery of the optimal microstructure representations with invariant variational autoencoders. CoRR Boris N. Slautin, Kamyar Barakati, Hiroshi Funakubo, Maxim A. Ziatdinov, Vladimir V. Shvartsman, Doru C. Lupascu, Sergei V. Kalinin
2025	J	`jnl`	Rewards-based image analysis in microscopy. CoRR Kamyar Barakati, Yu Liu, Utkarsh Pratiush, Boris N. Slautin, Sergei V. Kalinin
2025	J	`jnl`	SAM CoRR Kamyar Barakati, Utkarsh Pratiush, Sheryl Sanchez, Aditya Raghavan, Delia J. Milliron, Mahshid Ahmadi, Philip D. Rack, Sergei V. Kalinin
2025	J	`jnl`	The Power of the Pareto Front: Balancing Uncertain Rewards for Adaptive Experimentation in scanning probe microscopy. CoRR Yu Liu, Sergei V. Kalinin
2024	J	`jnl`	Active Deep Kernel Learning of Molecular Functionalities: Realizing Dynamic Structural Embeddings. CoRR Ayana Ghosh, Maxim A. Ziatdinov, Sergei V. Kalinin
2024	J	`jnl`	Automated Materials Discovery Platform Realized: Scanning Probe Microscopy of Combinatorial Libraries. CoRR Yu Liu, Rohit Pant, Ichiro Takeuchi, R. Jackson Spurling, Jon-Paul Maria, Maxim A. Ziatdinov, Sergei V. Kalinin
2024	J	`jnl`	Bayesian Co-navigation: Dynamic Designing of the Materials Digital Twins via Active Learning. CoRR Boris N. Slautin, Yongtao Liu, Hiroshi Funakubo, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin
2024	J	`jnl`	Building Workflows for Interactive Human in the Loop Automated Experiment (hAE) in STEM-EELS. CoRR Utkarsh Pratiush, Kevin M. Roccapriore, Yongtao Liu, Gerd Duscher, Maxim A. Ziatdinov, Sergei V. Kalinin
2024	J	`jnl`	Co-orchestration of Multiple Instruments to Uncover Structure-Property Relationships in Combinatorial Libraries. CoRR Boris N. Slautin, Utkarsh Pratiush, Ilia N. Ivanov, Yongtao Liu, Rohit Pant, Xiaohang Zhang, Ichiro Takeuchi, Maxim A. Ziatdinov, Sergei V. Kalinin
2024	J	`jnl`	Deep kernel methods learn better: from cards to process optimization. Mach. Learn. Sci. Technol. Mani Valleti, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin
2024	J	`jnl`	Implementing dynamic high-performance computing supported workflows on Scanning Transmission Electron Microscope. CoRR Utkarsh Pratiush, Austin Houston, Sergei V. Kalinin, Gerd Duscher
2024	J	`jnl`	Integration of Scanning Probe Microscope with High-Performance Computing: fixed-policy and reward-driven workflows implementation. CoRR Yu Liu, Utkarsh Pratiush, Jason Bemis, Roger Proksch, Reece Emery, Philip D. Rack, Yu-Chen Liu, Jan-Chi Yang, Stanislav Udovenko, Susan Trolier-McKinstry, Sergei V. Kalinin
2024	J	`jnl`	Invariant Discovery of Features Across Multiple Length Scales: Applications in Microscopy and Autonomous Materials Characterization. CoRR Aditya Raghavan, Utkarsh Pratiush, Mani Valleti, Richard Liu, Reece Emery, Hiroshi Funakubo, Yongtao Liu, Philip D. Rack, Sergei V. Kalinin
2024	J	`jnl`	Machine Learning-Based Reward-Driven Tuning of Scanning Probe Microscopy: Towards Fully Automated Microscopy. CoRR Yu Liu, RogerProksch, Jason Bemis, Utkarsh Pratiush, Astita Dubey, Mahshid Ahmadi, Reece Emery, Philip D. Rack, Yu-Chen Liu, Jan-Chi Yang, Sergei V. Kalinin
2024	J	`jnl`	Measurements with Noise: Bayesian Optimization for Co-optimizing Noise and Property Discovery in Automated Experiments. CoRR Boris N. Slautin, Yu Liu, Jan Dec, Vladimir V. Shvartsman, Doru C. Lupascu, Maxim A. Ziatdinov, Sergei V. Kalinin
2024	J	`jnl`	Physics-based reward driven image analysis in microscopy. CoRR Kamyar Barakati, Hui Yuan, Amit Goyal, Sergei V. Kalinin
2024	J	`jnl`	Predicting Battery Capacity Fade Using Probabilistic Machine Learning Models With and Without Pre-Trained Priors. CoRR Michael J. Kenney, Katerina G. Malollari, Sergei V. Kalinin, Maxim A. Ziatdinov
2024	J	`jnl`	Rapid optimization in high dimensional space by deep kernel learning augmented genetic algorithms. CoRR Mani Valleti, Aditya Raghavan, Sergei V. Kalinin
2024	J	`jnl`	Reward driven workflows for unsupervised explainable analysis of phases and ferroic variants from atomically resolved imaging data. CoRR Kamyar Barakati, Yu Liu, Chris Nelson, Maxim A. Ziatdinov, Xiaohang Zhang, Ichiro Takeuchi, Sergei V. Kalinin
2024	J	`jnl`	Toward Accelerating Discovery via Physics-Driven and Interactive Multifidelity Bayesian Optimization. J. Comput. Inf. Sci. Eng. Arpan Biswas, Mani Valleti, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin
2024	J	`jnl`	Towards accelerating physical discovery via non-interactive and interactive multi-fidelity Bayesian Optimization: Current challenges and future opportunities. CoRR Arpan Biswas, Sai Mani Prudhvi Valleti, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin
2024	J	`jnl`	Unraveling the Impact of Initial Choices and In-Loop Interventions on Learning Dynamics in Autonomous Scanning Probe Microscopy. CoRR Boris N. Slautin, Yongtao Liu, Hiroshi Funakubo, Sergei V. Kalinin
2024	J	`jnl`	Unsupervised Reward-Driven Image Segmentation in Automated Scanning Transmission Electron Microscopy Experiments. CoRR Kamyar Barakati, Utkarsh Pratiush, Austin Houston, Gerd Duscher, Sergei V. Kalinin
2023	J	`jnl`	A dynamic Bayesian optimized active recommender system for curiosity-driven Human-in-the-loop automated experiments. CoRR Arpan Biswas, Yongtao Liu, Nicole Creange, Yu-Chen Liu, Stephen Jesse, Jan-Chi Yang, Sergei V. Kalinin, Maxim A. Ziatdinov, Rama K. Vasudevan
2023	J	`jnl`	Autonomous scanning probe microscopy with hypothesis learning: Exploring the physics of domain switching in ferroelectric materials. Patterns Yongtao Liu, Anna N. Morozovska, Eugene A. Eliseev, Kyle P. Kelley, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin
2023	J	`jnl`	Combining Variational Autoencoders and Physical Bias for Improved Microscopy Data Analysis. CoRR Arpan Biswas, Maxim A. Ziatdinov, Sergei V. Kalinin
2023	J	`jnl`	Combining variational autoencoders and physical bias for improved microscopy data analysis Mach. Learn. Sci. Technol. Arpan Biswas, Maxim A. Ziatdinov, Sergei V. Kalinin
2023	J	`jnl`	Deep Kernel Methods Learn Better: From Cards to Process Optimization. CoRR Mani Valleti, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin
2023	J	`jnl`	Deep Learning for Automated Experimentation in Scanning Transmission Electron Microscopy. CoRR Sergei V. Kalinin, Debangshu Mukherjee, Kevin M. Roccapriore, Ben Blaiszik, Ayana Ghosh, Maxim A. Ziatdinov, Anees Al-Najjar, Christina Doty, Sarah Akers, Nageswara S. V. Rao, Joshua C. Agar, Steven R. Spurgeon
2023	J	`jnl`	Discovery of structure-property relations for molecules via hypothesis-driven active learning over the chemical space. CoRR Ayana Ghosh, Sergei V. Kalinin, Maxim A. Ziatdinov
2023	J	`jnl`	Explainability and human intervention in autonomous scanning probe microscopy. Patterns Yongtao Liu, Maxim A. Ziatdinov, Rama K. Vasudevan, Sergei V. Kalinin
2023	J	`jnl`	Exploring the Evolution of Metal Halide Perovskites via Latent Representations of the Photoluminescent Spectra. Adv. Intell. Syst. Sheryl Sanchez, Yongtao Liu, Jonghee Yang, Sergei V. Kalinin, Maxim A. Ziatdinov, Mahshid Ahmadi
2023	J	`jnl`	Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders Mach. Learn. Sci. Technol. Maxim A. Ziatdinov, Chun Yin Wong, Sergei V. Kalinin
2023	J	`jnl`	Human-in-the-loop: The future of Machine Learning in Automated Electron Microscopy. CoRR Sergei V. Kalinin, Yongtao Liu, Arpan Biswas, Gerd Duscher, Utkarsh Pratiush, Kevin Roccapriore, Maxim A. Ziatdinov, Rama K. Vasudevan
2023	J	`jnl`	Learning and Controlling Silicon Dopant Transitions in Graphene using Scanning Transmission Electron Microscopy. CoRR Max Schwarzer, Jesse Farebrother, Joshua Greaves, Ekin Dogus Cubuk, Rishabh Agarwal, Aaron C. Courville, Marc G. Bellemare, Sergei V. Kalinin, Igor Mordatch, Pablo Samuel Castro, Kevin M. Roccapriore
2023	J	`jnl`	Optimizing training trajectories in variational autoencoders via latent Bayesian optimization approach Mach. Learn. Sci. Technol. Arpan Biswas, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin
2023	J	`jnl`	Physics and Chemistry from Parsimonious Representations: Image Analysis via Invariant Variational Autoencoders. CoRR Mani Valleti, Yongtao Liu, Sergei V. Kalinin
2023	J	`jnl`	Probe microscopy is all you need Mach. Learn. Sci. Technol. Sergei V. Kalinin, Rama K. Vasudevan, Yongtao Liu, Ayana Ghosh, Kevin Roccapriore, Maxim A. Ziatdinov
2022	J	`jnl`	Active learning in open experimental environments: selecting the right information channel(s) based on predictability in deep kernel learning. CoRR Maxim A. Ziatdinov, Yongtao Liu, Sergei V. Kalinin
2022	J	`jnl`	AtomAI framework for deep learning analysis of image and spectroscopy data in electron and scanning probe microscopy. Nat. Mac. Intell. Maxim A. Ziatdinov, Ayana Ghosh, Chun Yin Wong, Sergei V. Kalinin
2022	J	`jnl`	Bayesian Active Learning for Scanning Probe Microscopy: from Gaussian Processes to Hypothesis Learning. CoRR Maxim A. Ziatdinov, Yongtao Liu, Kyle P. Kelley, Rama K. Vasudevan, Sergei V. Kalinin
2022	J	`jnl`	Discovering mechanisms for materials microstructure optimization via reinforcement learning of a generative model. Mach. Learn. Sci. Technol. Rama K. Vasudevan, Erick Orozco, Sergei V. Kalinin
2022	B	`conf`	Enabling Autonomous Electron Microscopy for Networked Computation and Steering. e-Science Anees Al-Najjar, Nageswara S. V. Rao, Ramanan Sankaran, Maxim A. Ziatdinov, Debangshu Mukherjee, Olga Ovchinnikova, Kevin Roccapriore, Andrew R. Lupini, Sergei V. Kalinin
2022	J	`jnl`	Enabling Autonomous Electron Microscopy for Networked Computation and Steering. CoRR Anees Al-Najjar, Nageswara S. V. Rao, Ramanan Sankaran, Maxim A. Ziatdinov, Debangshu Mukherjee, Olga Ovchinnikova, Kevin Roccapriore, Andrew R. Lupini, Sergei V. Kalinin
2022	J	`jnl`	Experimental discovery of structure-property relationships in ferroelectric materials via active learning. Nat. Mach. Intell. Yongtao Liu, Kyle P. Kelley, Rama K. Vasudevan, Hiroshi Funakubo, Maxim A. Ziatdinov, Sergei V. Kalinin
2022	—	`conf`	MLExchange: A web-based platform enabling exchangeable machine learning workflows for scientific studies. XLOOP@SC Zhuowen Zhao, Tanny Chavez, Elizabeth Holman, Guanhua Hao, Adam Green, Harinarayan Krishnan, Dylan McReynolds, Ronald Pandolfi, Eric J. Roberts, Petrus H. Zwart, Howard Yanxon, Nicholas Schwarz, Subramanian Sankaranarayanan, Sergei V. Kalinin, Apurva Mehta, Stuart Campbell, Alexander Hexemer
2022	J	`jnl`	MLExchange: A web-based platform enabling exchangeable machine learning workflows. CoRR Zhuowen Zhao, Tanny Chavez, Elizabeth Holman, Guanhua Hao, Adam Green, Harinarayan Krishnan, Dylan McReynolds, Ronald Pandolfi, Eric J. Roberts, Petrus H. Zwart, Howard Yanxon, Nicholas Schwarz, Subramanian Sankaranarayanan, Sergei V. Kalinin, Apurva Mehta, Stuart Campbell, Alexander Hexemer
2022	J	`jnl`	Microscopy is All You Need. CoRR Sergei V. Kalinin, Rama K. Vasudevan, Yongtao Liu, Ayana Ghosh, Kevin Roccapriore, Maxim A. Ziatdinov
2022	J	`jnl`	Optimizing Training Trajectories in Variational Autoencoders via Latent Bayesian Optimization Approach. CoRR Arpan Biswas, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin
2022	J	`jnl`	Physics makes the difference: Bayesian optimization and active learning via augmented Gaussian process. Mach. Learn. Sci. Technol. Maxim A. Ziatdinov, Ayana Ghosh, Sergei V. Kalinin
2022	J	`jnl`	Towards automating structural discovery in scanning transmission electron microscopy Mach. Learn. Sci. Technol. Nicole Creange, Ondrej Dyck, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin
2021	J	`jnl`	AtomAI: A Deep Learning Framework for Analysis of Image and Spectroscopy Data in (Scanning) Transmission Electron Microscopy and Beyond. CoRR Maxim A. Ziatdinov, Ayana Ghosh, Tommy Wong, Sergei V. Kalinin
2021	J	`jnl`	Automated and Autonomous Experiment in Electron and Scanning Probe Microscopy. CoRR Sergei V. Kalinin, Maxim A. Ziatdinov, Jacob D. Hinkle, Stephen Jesse, Ayana Ghosh, Kyle P. Kelley, Andrew R. Lupini, Bobby G. Sumpter, Rama K. Vasudevan
2021	B	`conf`	Building an Integrated Ecosystem of Computational and Observational Facilities to Accelerate Scientific Discovery. SMC Suhas Somnath, Rama K. Vasudevan, Stephen Jesse, Sergei V. Kalinin, Nageswara S. V. Rao, Christopher Brumgard, Feiyi Wang, Olga A. Kuchar, Arjun Shankar, Ben Mintz, Elke Arenholz, J. Robert Michael, Sarp Oral
2021	J	`jnl`	Decoding the shift-invariant data: applications for band-excitation scanning probe microscopy Mach. Learn. Sci. Technol. Yongtao Liu, Rama K. Vasudevan, Kyle K. Kelley, Dohyung Kim, Yogesh Sharma, Mahshid Ahmadi, Sergei V. Kalinin, Maxim A. Ziatdinov
2021	J	`jnl`	Decoding the shift-invariant data: applications for band-excitation scanning probe microscopy. CoRR Yongtao Liu, Rama K. Vasudevan, Kyle P. Kelley, Dohyung Kim, Yogesh Sharma, Mahshid Ahmadi, Sergei V. Kalinin, Maxim A. Ziatdinov
2021	J	`jnl`	Ensemble learning and iterative training (ELIT) machine learning: applications towards uncertainty quantification and automated experiment in atom-resolved microscopy. CoRR Ayana Ghosh, Bobby G. Sumpter, Ondrej Dyck, Sergei V. Kalinin, Maxim A. Ziatdinov
2021	J	`jnl`	Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders. CoRR Maxim A. Ziatdinov, Chun Yin Wong, Sergei V. Kalinin
2021	J	`jnl`	Propagation of priors for more accurate and efficient spectroscopic functional fits and their application to ferroelectric hysteresis. Mach. Learn. Sci. Technol. Nicole Creange, Kyle P. Kelley, C. Smith, D. Sando, Oliver Paull, N. Valanoor, S. Somnath, S. Jesse, Sergei V. Kalinin, Rama K. Vasudevan
2021	J	`jnl`	Robust Feature Disentanglement in Imaging Data via Joint Invariant Variational Autoencoders: from Cards to Atoms. CoRR Maxim A. Ziatdinov, Sergei V. Kalinin
2021	J	`jnl`	Semi-supervised learning of images with strong rotational disorder: assembling nanoparticle libraries. CoRR Maxim A. Ziatdinov, Muammer Yusuf Yaman, Yongtao Liu, David S. Ginger, Sergei V. Kalinin
2021	B	`conf`	Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing. SMC Pravallika Devineni, Panchapakesan Ganesh, Nikhil Sivadas, Abhijeet Dhakane, Ketan Maheshwari, Drahomira Herrmannova, Ramakrishnan Kannan, Seung-Hwan Lim, Thomas E. Potok, Jordan B. Chipka, Priyantha Mudalige, Mark Coletti, Sajal Dash, Arnab Kumar Paul, Sarp Oral, Feiyi Wang, Bill Kay, Melissa R. Allen-Dumas, Christa Brelsford, Joshua R. New, Andy Berres, Kuldeep R. Kurte, Jibonananda Sanyal, Levi Sweet, Chathika Gunaratne, Maxim A. Ziatdinov, Rama K. Vasudevan, Sergei V. Kalinin, Olivera Kotevska, Jean C. Bilheux, Hassina Z. Bilheux, Garrett E. Granroth, Thomas Proffen, Rick Riedel, Peter F. Peterson, Shruti R. Kulkarni, Kyle P. Kelley, Stephen Jesse, Maryam Parsa
2020	J	`jnl`	Deep learning of interface structures from simulated 4D STEM data: cation intermixing vs. roughening. Mach. Learn. Sci. Technol. M. P. Oxley, Junqi Yin, N. Borodinov, Suhas Somnath, Maxim A. Ziatdinov, Andrew R. Lupini, Stephen Jesse, Rama K. Vasudevan, Sergei V. Kalinin
2020	J	`jnl`	Estimating Preisach Density via Subset Selection. IEEE Access Xin Li, Dohyung Kim, Sabine M. Neumayer, Mahshid Ahmadi, Sergei V. Kalinin
2020	J	`jnl`	Off-the-shelf deep learning is not enough: parsimony, Bayes and causality. CoRR Rama K. Vasudevan, Maxim A. Ziatdinov, Lukas Vlcek, Sergei V. Kalinin
2018	A	`conf`	167-PFlops deep learning for electron microscopy: from learning physics to atomic manipulation. SC Robert M. Patton, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Don D. March, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Thomas P. Karnowski, Maxim A. Ziatdinov, Sergei V. Kalinin
2017	—	`conf`	Advances of the development of a ferroelectric field-effect transistor on Ge(001). ICICDT Patrick Ponath, Agham B. Posadas, Yuan Ren, Xiaoyu Wu, Keji Lai, Alex Demkov, Michael Schmidt, Ray Duffy, Paul K. Hurley, Jian Wang, Chadwin D. Young, Rama K. Vasudevan, M. Baris Okatan, Stephen Jesse, Sergei V. Kalinin
2016	Misc	`conf`	BEAM: A Computational Workflow System for Managing and Modeling Material Characterization Data in HPC Environments. ICCS Eric J. Lingerfelt, Alex Belianinov, Eirik Endeve, O. Ovchinnikov, Suhas Somnath, Jose M. Borreguero, N. Grodowitz, B. Park, Richard K. Archibald, Christopher T. Symons, Sergei V. Kalinin, O. E. Bronson Messer, Mallikarjun Shankar, Stephen Jesse
2015	J	`jnl`	What makes us a community: structure, correlations, and success in scientific world. CoRR Sergei V. Kalinin, Artem Maksov