Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  describe a deterministic anytime method for calculating filtered and smoothed distributions in large variable-based continuous time Markov processes. Prior non-random algorithms do not converge to the true distribution in the limit of infinite computation time. Sampling algorithms give different results each time run, which can lead to instability when used inside expectationmaximization or other algorithms. Our method combines the anytime convergent properties of sampling with the non-random nature of variational approaches. It is built upon a sum of timeordered products, an expansion of the matrix exponential.  demonstrate that our method performs as ll as or better than the current best sampling approaches on benchmark problems.
['E. Busra Celikkaya', 'Christian R. Shelton']
I am writing a research paper on a idea Deterministic Anytime Inference for Stochastic Continuous-Time Markov Processes
[{"from": "human", "value": "I am writing a research paper on a idea Deterministic Anytime Inference for Stochastic Continuous-Time Markov Processes"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  describe a deterministic anytime method for calculating filtered and smoothed distributions in large variable-based continuous time Markov processes. Prior non-random algorithms do not converge to the true distribution in the limit of infinite computation time. Sampling algorithms give different results each time run, which can lead to instability when used inside expectationmaximization or other algorithms. Our method combines the anytime convergent properties of sampling with the non-random nature of variational approaches. It is built upon a sum of timeordered products, an expansion of the matrix exponential.  demonstrate that our method performs as ll as or better than the current best sampling approaches on benchmark problems."}]