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Mikkel N. Schmidt

  1. Bayesian Community Detection
    2012/04/17 by Morten Mørup, Mikkel N. Schmidt · 5 citations
    Mathematics · Physics and Astronomy · #Complex Network Analysis Techniques #Opinion Dynamics and Social Influence #Stochastic processes and statistical mechanics
  2. Calibrated Uncertainty for Molecular Property Prediction using Ensembles\n of Message Passing Neural Networks
    2021/07/13 by Jonas Busk, Busk, Jonas, Peter Bjørn Jørgensen +9 · 4 citations
    Chemistry · Computer Science · Materials Science · #Computational Drug Discovery Methods #FOS: Computer and information sciences #History and advancements in chemistry #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Materials Science
  3. Neural Message Passing with Edge Updates for Predicting Properties of\n Molecules and Materials
    2018/06/08 by Peter Bjørn Jørgensen, Jørgensen, Peter Bjørn, Karsten W. Jacobsen +3 · 3 citations
    Computer Science · Materials Science · #Advanced Graph Neural Networks #Computational Drug Discovery Methods #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Materials Science
  4. Graph Neural Network Interatomic Potential Ensembles with Calibrated Aleatoric and Epistemic Uncertainty on Energy and Forces
    2023/05/10 by Jonas Busk, Busk, Jonas, Mikkel N. Schmidt +7 · 3 citations
    Computer Science · Engineering · Materials Science · #Advanced Graph Neural Networks #Chemical Physics (physics.chem-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Fuel Cells and Related Materials #Machine Learning (cs.LG) #Machine Learning in Materials Science
  5. Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity
    2023/06/22 by Bo Li, Li, Bo, Yasin Esfandiari +7 · 1 citation
    Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #Cryptography and Data Security #Distributed #FOS: Computer and information sciences #Machine Learning (cs.LG) #Parallel #Privacy-Preserving Technologies in Data #Stochastic Gradient Optimization Techniques #and Cluster Computing (cs.DC)
  6. Completely random measures for modelling block-structured networks
    2015/07/10 by Tue Herlau, Mikkel N. Schmidt, Herlau, Tue +3 · 1 citation
    Mathematics · Physics and Astronomy · #Complex Network Analysis Techniques #FOS: Computer and information sciences #Machine Learning (stat.ML) #Opinion Dynamics and Social Influence #Stochastic processes and statistical mechanics
  7. FreqRISE: Explaining time series using frequency masking
    2024/06/19 by Thea Brüsch, Kristoffer Wickstrøm, Brüsch, Thea +7 · 1 citation
    Computer Science · Decision Sciences · #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Stock Market Forecasting Methods #Time Series Analysis and Forecasting
  8. Semi-Supervised Learning for Molecular Graphs via Ensemble Consensus
    2026/07/30 by Rasmus Tirsgaard, Laurits Fredsgaard, Marisa Wodrich +2
    Computer Science · #cs.LG