Runa Eschenhagen

Publications by Year

Research Areas

Gaussian Processes and Bayesian Inference, Neural Networks and Applications, Domain Adaptation and Few-Shot Learning, Stochastic Gradient Optimization Techniques, Adversarial Robustness in Machine Learning

Most-Cited Works

• Practical Deep Learning with Bayesian Principles(2019)
• → Continual Deep Learning by Functional Regularisation of Memorable Past(2020)32 cited
• → Laplace Redux -- Effortless Bayesian Deep Learning(2021)27 cited
• → Benchmarking Neural Network Training Algorithms(2023)6 cited
• → Approximate Bayesian Neural Operators: Uncertainty Quantification for Parametric PDEs(2022)4 cited
• → Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures(2023)2 cited
• → Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks(2022)2 cited
• → Mixtures of Laplace Approximations for Improved Post-Hoc Uncertainty in Deep Learning(2021)2 cited