Kersting, Hans

1. Probabilistic Solutions To Ordinary Differential Equations As Non-Linear Bayesian Filtering: A New Perspective
   2018/10/08 by Filip Tronarp, Hans Kersting, Tronarp, Filip +5 · 8 citations
   Computer Science · Engineering · #Computation (stat.CO) #FOS: Computer and information sciences #Machine Learning (stat.ML) #Methodology (stat.ME)
2. Convergence Rates of Gaussian ODE Filters
   2018/07/25 by Kersting, Hans, Sullivan, T. J., Hennig, Philipp · 3 citations
   #60G15 #60J70 #62G20 #62M05 #65C20 #65L05 #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Numerical Analysis (math.NA) #Statistics Theory (math.ST)
3. Explicit Regularization in Overparametrized Models via Noise Injection
   2022/06/09 by Orvieto, Antonio, Raj, Anant, Kersting, Hans +1 · 4 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
4. An SDE for Modeling SAM: Theory and Insights
   2023/01/19 by Enea Monzio Compagnoni, Compagnoni, Enea Monzio, Luca Biggio +9 · 3 citations
   Computer Science · Decision Sciences · Mathematics · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Markov Chains and Monte Carlo Methods #Optimization and Control (math.OC) #Stochastic Gradient Optimization Techniques
5. Anticorrelated Noise Injection for Improved Generalization
   2022/02/06 by Orvieto, Antonio, Kersting, Hans, Proske, Frank +2 · 2 citations
   #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
6. Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free'\n Dynamical Systems
   2020/02/21 by Hans Kersting, Kersting, Hans, Nicholas Krämer +9 · 1 citation
   Computer Science · Mathematics · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Markov Chains and Monte Carlo Methods #Methodology (stat.ME) #Model Reduction and Neural Networks #Numerical Analysis (math.NA)