42 citations · 141 across the 10 of their papers we have counts for
3 papers · 1 filter
Learning Probabilistic Filters with Strictly Proper Scoring Rules
Eviatar Bach, Ricardo Baptista, Jochen Bröcker +2
Bayesian filtering of partially and noisily observed dynamical systems seeks to infer the evolving conditional distribution of the state of a dynamical system given observations, i…
Learning Optimal Filters Using Variational Inference
Eviatar Bach, Ricardo Baptista, Enoch Luk +1
Filtering - the task of estimating the conditional distribution for states of a dynamical system given partial and noisy observations - is important in many areas of science and en…
Deep learning-enhanced ensemble-based data assimilation for high-dimensional nonlinear dynamical systems
Ashesh Chattopadhyay, Ebrahim Nabizadeh, Eviatar Bach +1
Data assimilation (DA) is a key component of many forecasting models in science and engineering. DA allows one to estimate better initial conditions using an imperfect dynamical mo…