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Runa Eschenhagen

  1. Benchmarking Neural Network Training Algorithms
    2023/06/12 by George E. Dahl, Frank Schneider, Dahl, George E. +47 · 2 voices · 8 citations
    Computer Science · Mathematics · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Stochastic Gradient Optimization Techniques #cs.LG #stat.ML
  2. Laplace Redux -- Effortless Bayesian Deep Learning
    2021/06/28 by Erik Daxberger, Agustinus Kristiadi, Daxberger, Erik +9 · 35 citations
    Computer Science · #Gaussian Processes and Bayesian Inference #Machine Learning and Algorithms #Domain Adaptation and Few-Shot Learning
  3. Continual Deep Learning by Functional Regularisation of Memorable Past
    2020/04/29 by Pingbo Pan, Pan, Pingbo, Siddharth Swaroop +9 · 6 citations
    Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
  4. Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures
    2023/11/01 by Runa Eschenhagen, Eschenhagen, Runa, Alexander Immer +7 · 8 citations
    Computer Science · #Advanced Neural Network Applications #Stochastic Gradient Optimization Techniques #Machine Learning and Data Classification
  5. Approximate Bayesian Neural Operators: Uncertainty Quantification for Parametric PDEs
    2022/08/02 by Emilia Magnani, Magnani, Emilia, Nicholas Krämer +7 · 5 citations
    Computer Science · Engineering · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Numerical Analysis (math.NA) #Reservoir Engineering and Simulation Methods
  6. Influence Functions for Scalable Data Attribution in Diffusion Models
    2024/10/17 by Bruno Mlodozeniec, Mlodozeniec, Bruno, Runa Eschenhagen +9 · 6 citations
    Computer Science · Physics and Astronomy · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural Networks and Applications #Opinion Dynamics and Social Influence
  7. Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective
    2024/02/05 by Lin Wu, Felix Dangel, Lin, Wu +9 · 4 citations
    Mathematics · #Advanced Optimization Algorithms Research #FOS: Computer and information sciences #FOS: Mathematics #Iterative Methods for Nonlinear Equations #Machine Learning (cs.LG) #Numerical methods in inverse problems #Optimization and Control (math.OC)
  8. Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks
    2022/05/20 by Agustinus Kristiadi, Runa Eschenhagen, Kristiadi, Agustinus +3 · 1 citation
    Computer Science · Physics and Astronomy · #Adversarial Robustness in Machine Learning #Model Reduction and Neural Networks #Gaussian Processes and Bayesian Inference
  9. Structured Inverse-Free Natural Gradient: Memory-Efficient & Numerically-Stable KFAC
    2023/12/09 by Lin Wu, Lin, Wu, Felix Dangel +11 · 1 citation
    Computer Science · Earth and Planetary Sciences · Physics and Astronomy · #FOS: Computer and information sciences #Geophysical and Geoelectrical Methods #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Matrix Theory and Algorithms #Model Reduction and Neural Networks