Sergei V. Kalinin

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 53

Top Topics

Gaussian Processes

Electron Microscopy

Top Venues

Mach. Learn. Sci. Technol.

Publications

Ayana Ghosh, Maxim A. Ziatdinov, Sergei V. Kalinin
Active Deep Kernel Learning of Molecular Functionalities: Realizing Dynamic Structural Embeddings. CoRR (2024)
Utkarsh Pratiush, Austin Houston, Sergei V. Kalinin, Gerd Duscher
Implementing dynamic high-performance computing supported workflows on Scanning Transmission Electron Microscope. CoRR (2024)
Boris N. Slautin, Utkarsh Pratiush, Ilia N. Ivanov, Yongtao Liu, Rohit Pant, Xiaohang Zhang, Ichiro Takeuchi, Maxim A. Ziatdinov, Sergei V. Kalinin
Multimodal Co-orchestration for Exploring Structure-Property Relationships in Combinatorial Libraries via Multi-Task Bayesian Optimization. CoRR (2024)
Mani Valleti, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin
Deep kernel methods learn better: from cards to process optimization. Mach. Learn. Sci. Technol. 5 (1) (2024)
Boris N. Slautin, Yongtao Liu, Hiroshi Funakubo, Sergei V. Kalinin
Unraveling the Impact of Initial Choices and In-Loop Interventions on Learning Dynamics in Autonomous Scanning Probe Microscopy. CoRR (2024)
Arpan Biswas, Sai Mani Prudhvi Valleti, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin
Towards accelerating physical discovery via non-interactive and interactive multi-fidelity Bayesian Optimization: Current challenges and future opportunities. CoRR (2024)
Boris N. Slautin, Yongtao Liu, Hiroshi Funakubo, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin
Bayesian Co-navigation: Dynamic Designing of the Materials Digital Twins via Active Learning. CoRR (2024)
Utkarsh Pratiush, Kevin M. Roccapriore, Yongtao Liu, Gerd Duscher, Maxim A. Ziatdinov, Sergei V. Kalinin
Building Workflows for Interactive Human in the Loop Automated Experiment (hAE) in STEM-EELS. CoRR (2024)
Kamyar Barakati, Hui Yuan, Amit Goyal, Sergei V. Kalinin
Physics-based reward driven image analysis in microscopy. CoRR (2024)
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
Integration of Scanning Probe Microscope with High-Performance Computing: fixed-policy and reward-driven workflows implementation. CoRR (2024)
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
Learning and Controlling Silicon Dopant Transitions in Graphene using Scanning Transmission Electron Microscopy. CoRR (2023)
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
Deep Learning for Automated Experimentation in Scanning Transmission Electron Microscopy. CoRR (2023)
Arpan Biswas, Maxim A. Ziatdinov, Sergei V. Kalinin
. Mach. Learn. Sci. Technol. 4 (4) (2023)
Maxim A. Ziatdinov, Chun Yin Wong, Sergei V. Kalinin
. Mach. Learn. Sci. Technol. 4 (4) (2023)
Sergei V. Kalinin, Yongtao Liu, Arpan Biswas, Gerd Duscher, Utkarsh Pratiush, Kevin Roccapriore, Maxim A. Ziatdinov, Rama K. Vasudevan
Human-in-the-loop: The future of Machine Learning in Automated Electron Microscopy. CoRR (2023)
Yongtao Liu, Maxim A. Ziatdinov, Rama K. Vasudevan, Sergei V. Kalinin
Explainability and human intervention in autonomous scanning probe microscopy. Patterns 4 (11) (2023)
Arpan Biswas, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin
. Mach. Learn. Sci. Technol. 4 (1) (2023)
Yongtao Liu, Anna N. Morozovska, Eugene A. Eliseev, Kyle P. Kelley, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin
Autonomous scanning probe microscopy with hypothesis learning: Exploring the physics of domain switching in ferroelectric materials. Patterns 4 (3) (2023)
Mani Valleti, Yongtao Liu, Sergei V. Kalinin
Physics and Chemistry from Parsimonious Representations: Image Analysis via Invariant Variational Autoencoders. CoRR (2023)
Arpan Biswas, Maxim A. Ziatdinov, Sergei V. Kalinin
Combining Variational Autoencoders and Physical Bias for Improved Microscopy Data Analysis. CoRR (2023)
Arpan Biswas, Yongtao Liu, Nicole Creange, Yu-Chen Liu, Stephen Jesse, Jan-Chi Yang, Sergei V. Kalinin, Maxim A. Ziatdinov, Rama K. Vasudevan
A dynamic Bayesian optimized active recommender system for curiosity-driven Human-in-the-loop automated experiments. CoRR (2023)
Sheryl Sanchez, Yongtao Liu, Jonghee Yang, Sergei V. Kalinin, Maxim A. Ziatdinov, Mahshid Ahmadi
Exploring the Evolution of Metal Halide Perovskites via Latent Representations of the Photoluminescent Spectra. Adv. Intell. Syst. 5 (5) (2023)
Mani Valleti, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin
Deep Kernel Methods Learn Better: From Cards to Process Optimization. CoRR (2023)
Ayana Ghosh, Sergei V. Kalinin, Maxim A. Ziatdinov
Discovery of structure-property relations for molecules via hypothesis-driven active learning over the chemical space. CoRR (2023)
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
MLExchange: A web-based platform enabling exchangeable machine learning workflows. CoRR (2022)
Yongtao Liu, Kyle P. Kelley, Rama K. Vasudevan, Hiroshi Funakubo, Maxim A. Ziatdinov, Sergei V. Kalinin
Experimental discovery of structure-property relationships in ferroelectric materials via active learning. Nat. Mach. Intell. 4 (4) (2022)
Maxim A. Ziatdinov, Yongtao Liu, Kyle P. Kelley, Rama K. Vasudevan, Sergei V. Kalinin
Bayesian Active Learning for Scanning Probe Microscopy: from Gaussian Processes to Hypothesis Learning. CoRR (2022)
Maxim A. Ziatdinov, Ayana Ghosh, Chun Yin Wong, Sergei V. Kalinin
AtomAI framework for deep learning analysis of image and spectroscopy data in electron and scanning probe microscopy. Nat. Mac. Intell. 4 (12) (2022)
Anees Al-Najjar, Nageswara S. V. Rao, Ramanan Sankaran, Maxim A. Ziatdinov, Debangshu Mukherjee, Olga Ovchinnikova, Kevin Roccapriore, Andrew R. Lupini, Sergei V. Kalinin
Enabling Autonomous Electron Microscopy for Networked Computation and Steering. e-Science (2022)
Maxim A. Ziatdinov, Yongtao Liu, Sergei V. Kalinin
Active learning in open experimental environments: selecting the right information channel(s) based on predictability in deep kernel learning. CoRR (2022)
Rama K. Vasudevan, Erick Orozco, Sergei V. Kalinin
Discovering mechanisms for materials microstructure optimization via reinforcement learning of a generative model. Mach. Learn. Sci. Technol. 3 (4) (2022)
Nicole Creange, Ondrej Dyck, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin
. Mach. Learn. Sci. Technol. 3 (1) (2022)
Arpan Biswas, Rama K. Vasudevan, Maxim A. Ziatdinov, Sergei V. Kalinin
Optimizing Training Trajectories in Variational Autoencoders via Latent Bayesian Optimization Approach. CoRR (2022)
Maxim A. Ziatdinov, Ayana Ghosh, Sergei V. Kalinin
Physics makes the difference: Bayesian optimization and active learning via augmented Gaussian process. Mach. Learn. Sci. Technol. 3 (1) (2022)
Sergei V. Kalinin, Rama K. Vasudevan, Yongtao Liu, Ayana Ghosh, Kevin Roccapriore, Maxim A. Ziatdinov
Microscopy is All You Need. CoRR (2022)
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
MLExchange: A web-based platform enabling exchangeable machine learning workflows for scientific studies. XLOOP@SC (2022)
Anees Al-Najjar, Nageswara S. V. Rao, Ramanan Sankaran, Maxim A. Ziatdinov, Debangshu Mukherjee, Olga Ovchinnikova, Kevin Roccapriore, Andrew R. Lupini, Sergei V. Kalinin
Enabling Autonomous Electron Microscopy for Networked Computation and Steering. CoRR (2022)
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
Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing. SMC (2021)
Maxim A. Ziatdinov, Chun Yin Wong, Sergei V. Kalinin
Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders. CoRR (2021)
Ayana Ghosh, Bobby G. Sumpter, Ondrej Dyck, Sergei V. Kalinin, Maxim A. Ziatdinov
Ensemble learning and iterative training (ELIT) machine learning: applications towards uncertainty quantification and automated experiment in atom-resolved microscopy. CoRR (2021)
Yongtao Liu, Rama K. Vasudevan, Kyle P. Kelley, Dohyung Kim, Yogesh Sharma, Mahshid Ahmadi, Sergei V. Kalinin, Maxim A. Ziatdinov
Decoding the shift-invariant data: applications for band-excitation scanning probe microscopy. CoRR (2021)
Yongtao Liu, Rama K. Vasudevan, Kyle K. Kelley, Dohyung Kim, Yogesh Sharma, Mahshid Ahmadi, Sergei V. Kalinin, Maxim A. Ziatdinov
. Mach. Learn. Sci. Technol. 2 (4) (2021)
Suhas Somnath, Rama K. Vasudevan, Stephen Jesse, Sergei V. Kalinin, Nageswara S. V. Rao, Christopher Brumgard, Feiyi Wang, Olga Kuchar, Arjun Shankar, Ben Mintz, Elke Arenholz, J. Robert Michael, Sarp Oral
Building an Integrated Ecosystem of Computational and Observational Facilities to Accelerate Scientific Discovery. SMC (2021)
Maxim A. Ziatdinov, Sergei V. Kalinin
Robust Feature Disentanglement in Imaging Data via Joint Invariant Variational Autoencoders: from Cards to Atoms. CoRR (2021)
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
Automated and Autonomous Experiment in Electron and Scanning Probe Microscopy. CoRR (2021)
Nicole Creange, Kyle P. Kelley, C. Smith, D. Sando, O. Paull, N. Valanoor, S. Somnath, S. Jesse, Sergei V. Kalinin, Rama K. Vasudevan
Propagation of priors for more accurate and efficient spectroscopic functional fits and their application to ferroelectric hysteresis. Mach. Learn. Sci. Technol. 2 (4) (2021)
Maxim A. Ziatdinov, Ayana Ghosh, Tommy Wong, Sergei V. Kalinin
AtomAI: A Deep Learning Framework for Analysis of Image and Spectroscopy Data in (Scanning) Transmission Electron Microscopy and Beyond. CoRR (2021)
Maxim A. Ziatdinov, Muammer Yusuf Yaman, Yongtao Liu, David Ginger, Sergei V. Kalinin
Semi-supervised learning of images with strong rotational disorder: assembling nanoparticle libraries. CoRR (2021)
M. P. Oxley, Junqi Yin, N. Borodinov, Suhas Somnath, Maxim A. Ziatdinov, Andrew R. Lupini, Stephen Jesse, Rama K. Vasudevan, Sergei V. Kalinin
Deep learning of interface structures from simulated 4D STEM data: cation intermixing vs. roughening. Mach. Learn. Sci. Technol. 1 (4) (2020)
Rama K. Vasudevan, Maxim A. Ziatdinov, Lukas Vlcek, Sergei V. Kalinin
Off-the-shelf deep learning is not enough: parsimony, Bayes and causality. CoRR (2020)
Xin Li, Dohyung Kim, Sabine M. Neumayer, Mahshid Ahmadi, Sergei V. Kalinin
Estimating Preisach Density via Subset Selection. IEEE Access 8 (2020)
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
167-PFlops deep learning for electron microscopy: from learning physics to atomic manipulation. SC (2018)
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
Advances of the development of a ferroelectric field-effect transistor on Ge(001). ICICDT (2017)
Sergei V. Kalinin, Artem Maksov
What makes us a community: structure, correlations, and success in scientific world. CoRR (2015)