Pradeep Bajracharya
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    • Pandas
    • PyTorch
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  • Publications
    • cAPM: Continual AI-Assisted Pace-Mapping with Active Learning
    • Gradient-based active learning for intelligent discovery of colloidal phase diagrams
    • ROSE: RADICAL Orchestrator for Surrogate Exploration
    • AI-Assisted Pace-Mapping using Continual-Learning Methods in Bayesian Optimization
    • Meta-learning based Active Learning Approach for Computer-Assisted Pace-Mapping
    • On the interdependence between data selection and architecture optimization in deep active learning
    • Feasibility study on active learning of smart surrogates for scientific simulations
    • Active learning based Cardiac Tissue Parameter Estimation for Personalized model exploiting predictive uncertainty
    • Fast Posterior Estimation of Cardiac Electrophysiological Model Parameters via Bayesian Active Learning
    • Semi-supervised Medical Image Classification with Global Latent Mixing
    • Embedding High-dimensional Bayesian Optimization via Generative Modeling: Parameter Personalization of Cardiac Electrophysiological Models
    • Indoor Odometry and Point Cloud Mapping
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Pandas

Oct 26, 2023 · 1 min read
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Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures.

Last updated on Aug 1, 2026
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Pradeep Bajracharya
Authors
Pradeep Bajracharya (he/him)
Postdoctoral Scholar
PyTorch Oct 26, 2023 →

© {2026} Pradeep Bajracharya. This work is licensed under CC BY NC ND 4.0

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