Frederik Kunstner

1. Limitations of the Empirical Fisher Approximation for Natural Gradient Descent
   2019/05/29 by Frederik Künstner, Frederik Kunstner, Kunstner, Frederik +4 · 32 citations
   Computer Science · Engineering · Mathematics · #FOS: Computer and information sciences #Face and Expression Recognition #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #cs.LG #stat.ML
2. Noise Is Not the Main Factor Behind the Gap Between SGD and Adam on Transformers, but Sign Descent Might Be
   2023/04/27 by Frederik Kunstner, Frederik Künstner, Kunstner, Frederik +6 · 1 voice · 22 citations
   Computer Science · Mathematics · #Advanced Neural Network Applications #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Metaheuristic Optimization Algorithms Research #Neural Networks and Applications #Optimization and Control (math.OC) #cs.LG #math.OC
3. BackPACK: Packing more into backprop
   2019/12/23 by Felix Dangel, Frederik Künstner, Frederik Kunstner +4 · 7 citations
   Computer Science · Engineering · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #Tensor decomposition and applications #cs.LG #stat.ML
4. SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient
   2018/11/11 by Aaron Mishkin, Frederik Kunstner, Mishkin, Aaron +8 · 7 citations
   Computer Science · Mathematics · #Artificial Intelligence (cs.AI) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #cs.AI #cs.LG #stat.ML