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Schmon, Sebastian M.

  1. Investigating the Impact of Model Misspecification in Neural Simulation-based Inference
    2022/09/05 by Cannon, Patrick, Ward, Daniel, Schmon, Sebastian M. · 7 citations
    #Computation (stat.CO) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  2. Capturing Label Characteristics in VAEs
    2020/06/17 by Tom Joy, Joy, Tom, Sebastian M. Schmon +6 · 2 citations
    Computer Science · #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Human Pose and Action Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Healthcare
  3. Large Sample Asymptotics of the Pseudo-Marginal Method
    2018/06/26 by Schmon, Sebastian M., Deligiannidis, George, Doucet, Arnaud +1 · 1 citation
    #Computation (stat.CO) #FOS: Computer and information sciences
  4. Learning Multimodal VAEs through Mutual Supervision
    2021/06/23 by Joy, Tom, Shi, Yuge, Torr, Philip H. S. +3 · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  5. Calibrating Agent-based Models to Microdata with Graph Neural Networks
    2022/06/15 by Joel Dyer, Patrick Cannon, Dyer, Joel +5 · 1 citation
    Computer Science · Engineering · Physics and Astronomy · #Time Series Analysis and Forecasting #Traffic Prediction and Management Techniques #Complex Network Analysis Techniques
  6. Latent-X: An Atom-level Frontier Model for De Novo Protein Binder Design
    2025/07/25 by Latent Labs Team, Bridgland, Alex, Crabbé, Jonathan +13 · 4 citations
    #Biomolecules (q-bio.BM) #FOS: Biological sciences