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Foong, Andrew Y. K.

  1. Fast protein backbone generation with SE(3) flow matching
    2023/10/08 by Jason Yim, Andrew M. Campbell, Andrew Campbell +21 · 1 voice · 24 citations
    Biochemistry, Genetics and Molecular Biology · Decision Sciences · Physics and Astronomy · #Model Reduction and Neural Networks #Protein Structure and Dynamics #Scientific Computing and Data Management #q-bio.QM
  2. Convolutional Conditional Neural Processes
    2019/10/29 by Gordon, Jonathan, Bruinsma, Wessel P., Foong, Andrew Y. K. +3 · 10 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  3. Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics
    2023/02/02 by Leon Klein, Klein, Leon, Andrew Y. K. Foong +13 · 12 citations
    Biochemistry, Genetics and Molecular Biology · Chemistry · Materials Science · #Chemical Physics (physics.chem-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Materials Science #Mass Spectrometry Techniques and Applications #Protein Structure and Dynamics #Statistical Mechanics (cond-mat.stat-mech)
  4. Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes
    2020/07/02 by Andrew Y. K. Foong, Wessel P. Bruinsma, Foong, Andrew Y. K. +9 · 5 citations
    Computer Science · #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Time Series Analysis and Forecasting
  5. Autoregressive Conditional Neural Processes
    2023/03/25 by Wessel P. Bruinsma, Bruinsma, Wessel P., Stratis Markou +15 · 5 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  6. 'In-Between' Uncertainty in Bayesian Neural Networks
    2019/06/27 by Foong, Andrew Y. K., Li, Yingzhen, Hernández-Lobato, José Miguel +1 · 2 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  7. The Gaussian Neural Process
    2021/01/10 by Wessel P. Bruinsma, James Requeima, Bruinsma, Wessel P. +7 · 4 citations
    Computer Science · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
  8. Denoising Diffusion Probabilistic Models in Six Simple Steps
    2024/02/06 by Richard E. Turner, Cristiana-Diana Diaconu, Turner, Richard E. +9 · 1 voice · 3 citations
    Computer Science · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #cs.LG #stat.ML
  9. How Tight Can PAC-Bayes be in the Small Data Regime?
    2021/06/07 by Andrew Y. K. Foong, Wessel P. Bruinsma, Foong, Andrew Y. K. +5 · 1 citation
    Computer Science · Engineering · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Sparse and Compressive Sensing Techniques #Statistics Theory (math.ST)