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Table representation of search results timeline featuring number of search results per year.

Year Number of Results
1946 1
1948 2
1949 2
1950 1
1951 1
1952 4
1953 6
1954 5
1955 7
1956 7
1957 7
1958 7
1959 7
1960 11
1961 7
1962 8
1963 2
1964 6
1965 6
1966 8
1967 4
1970 3
1971 6
1973 4
1974 6
1975 1
1976 1
1977 2
1978 4
1979 2
1980 2
1981 5
1982 5
1983 7
1984 7
1985 2
1986 2
1987 2
1988 2
1989 1
1990 5
1991 9
1992 4
1993 6
1994 6
1995 13
1996 17
1997 19
1998 18
1999 10
2000 9
2001 10
2002 9
2003 7
2004 5
2005 14
2006 11
2007 10
2008 12
2009 12
2010 11
2011 9
2012 16
2013 14
2014 17
2015 25
2016 21
2017 43
2018 51
2019 36
2020 26
2021 41
2022 57
2023 55
2024 60
2025 29

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812 results

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Page 1
Synchronization in a multilevel network using the Hamilton-Jacobi-Bellman (HJB) technique.
Njougouo T, Camargo V, Louodop P, Fagundes Ferreira F, Talla PK, Cerdeira HA. Njougouo T, et al. Chaos. 2022 Sep;32(9):093133. doi: 10.1063/5.0088880. Chaos. 2022. PMID: 36182367
This paper presents the optimal control and synchronization problem of a multilevel network of Rossler chaotic oscillators. Using the Hamilton-Jacobi-Bellman technique, the optimal control law with a three-state variable feedback is designed such that the trajectories of a …
This paper presents the optimal control and synchronization problem of a multilevel network of Rossler chaotic oscillators. Using the Hamilt …
Sample path properties of the average generation of a Bellman-Harris process.
Meli G, Weber TS, Duffy KR. Meli G, et al. J Math Biol. 2019 Jul;79(2):673-704. doi: 10.1007/s00285-019-01373-0. Epub 2019 May 8. J Math Biol. 2019. PMID: 31069504
Motivated by a recently proposed design for a DNA coded randomised algorithm that enables inference of the average generation of a collection of cells descendent from a common progenitor, here we establish strong convergence properties for the average generation of a super-critic …
Motivated by a recently proposed design for a DNA coded randomised algorithm that enables inference of the average generation of a collectio …
A Hamilton-Jacobi-Bellman approach for termination of seizure-like bursting.
Wilson D, Moehlis J. Wilson D, et al. J Comput Neurosci. 2014 Oct;37(2):345-55. doi: 10.1007/s10827-014-0507-7. Epub 2014 Jun 26. J Comput Neurosci. 2014. PMID: 24965911 Free PMC article.
We use Hamilton-Jacobi-Bellman methods to find minimum-time and energy-optimal control strategies to terminate seizure-like bursting behavior in a conductance-based neural model. ...
We use Hamilton-Jacobi-Bellman methods to find minimum-time and energy-optimal control strategies to terminate seizure-like bursting …
A Hamilton-Jacobi-Bellman approach to high angular resolution diffusion tractography.
Pichon E, Westin CF, Tannenbaum AR. Pichon E, et al. Med Image Comput Comput Assist Interv. 2005;8(Pt 1):180-7. doi: 10.1007/11566465_23. Med Image Comput Comput Assist Interv. 2005. PMID: 16685844 Free PMC article.
Minimum cost curves are determined by solving the Hamilton-Jacobi-Bellman using an efficient algorithm. Classical costs based on the diffusion tensor field can be seen as a special case. ...
Minimum cost curves are determined by solving the Hamilton-Jacobi-Bellman using an efficient algorithm. Classical costs based on the …
Bellman's GAP--a language and compiler for dynamic programming in sequence analysis.
Sauthoff G, Möhl M, Janssen S, Giegerich R. Sauthoff G, et al. Bioinformatics. 2013 Mar 1;29(5):551-60. doi: 10.1093/bioinformatics/btt022. Epub 2013 Jan 25. Bioinformatics. 2013. PMID: 23355290 Free PMC article.
RESULTS: In Bellman's GAP, dynamic programming algorithms are described in a declarative style by tree grammars, evaluation algebras and products formed thereof. ...Finally, it evaluates Bellman's GAP as an implementation platform of 'real-world' bioinformatics tool …
RESULTS: In Bellman's GAP, dynamic programming algorithms are described in a declarative style by tree grammars, evaluation algebras …
Bellman-Steffensen type inequalities.
Jakšetić J, Pečarić J, Smoljak Kalamir K. Jakšetić J, et al. J Inequal Appl. 2018;2018(1):288. doi: 10.1186/s13660-018-1882-9. Epub 2018 Oct 22. J Inequal Appl. 2018. PMID: 30839733 Free PMC article.
In this paper some Bellman-Steffensen type inequalities are generalized for positive measures. Using sublinearity of a class of convex functions and Jensen's inequality, nonnormalized versions of Steffensen's inequality are obtained. Further, linear functionals, from obtai …
In this paper some Bellman-Steffensen type inequalities are generalized for positive measures. Using sublinearity of a class of conve …
Modeling Bellman-error with logistic distribution with applications in reinforcement learning.
Lv O, Zhou B, Yang LF. Lv O, et al. Neural Netw. 2024 Sep;177:106387. doi: 10.1016/j.neunet.2024.106387. Epub 2024 May 15. Neural Netw. 2024. PMID: 38788292
In modern Reinforcement Learning (RL) approaches, optimizing the Bellman error is a critical element across various algorithms, notably in deep Q-Learning and related methodologies. Traditional approaches predominantly employ the mean-squared Bellman error (MSELoss) …
In modern Reinforcement Learning (RL) approaches, optimizing the Bellman error is a critical element across various algorithms, notab …
DPB-NBFnet: Using neural Bellman-Ford networks to predict DNA-protein binding.
Li J, Zhuo L, Lian X, Pan S, Xu L. Li J, et al. Front Pharmacol. 2022 Oct 28;13:1018294. doi: 10.3389/fphar.2022.1018294. eCollection 2022. Front Pharmacol. 2022. PMID: 36386160 Free PMC article.
Our work possesses the same motivation and we put the latest Neural Bellman-Ford neural networks (NBFnets) into use to build pair representations of DNA and protein to predict the existence of DNA-protein binding (DPB). NBFnet is a graph neural network model that uses the …
Our work possesses the same motivation and we put the latest Neural Bellman-Ford neural networks (NBFnets) into use to build pair rep …
Pandemic portfolio choice.
Kraft H, Weiss F. Kraft H, et al. Eur J Oper Res. 2023 Feb 16;305(1):451-462. doi: 10.1016/j.ejor.2022.05.035. Epub 2022 May 25. Eur J Oper Res. 2023. PMID: 35651517 Free PMC article.
The corresponding stochastic dynamic optimization problem is complex: It is characterized by a system of Hamilton-Jacobi-Bellman equations which are coupled with optimality conditions that are only given implicitly. ...
The corresponding stochastic dynamic optimization problem is complex: It is characterized by a system of Hamilton-Jacobi-Bellman equa …
Robust Losses for Learning Value Functions.
Patterson A, Liao V, White M. Patterson A, et al. IEEE Trans Pattern Anal Mach Intell. 2023 May;45(5):6157-6167. doi: 10.1109/TPAMI.2022.3213503. Epub 2023 Apr 3. IEEE Trans Pattern Anal Mach Intell. 2023. PMID: 36227822
Most value function learning algorithms in reinforcement learning are based on the mean squared (projected) Bellman error. However, squared errors are known to be sensitive to outliers, both skewing the solution of the objective and resulting in high-magnitude and high-var …
Most value function learning algorithms in reinforcement learning are based on the mean squared (projected) Bellman error. However, s …
812 results