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121

Metodología y algoritmo para encontrar números perfectos en un rango determinado de números naturales usando Programación Funcional.
Trejos, O. I.
Entre Ciencia e Ingeniería. ene-jun2017, Vol. 11 Issue 21, p66-72. 7p.

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122

Program Synthesis using Conflict-Driven Learning
Feng, Yu ; Martins, Ruben ; Bastani, Osbert ; et al.

Computer Science - Progr...
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123

Chapter 13 - Prospects
In Foundations of Quantum Programming Edition: Second Edition. 2024:367-373

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124

Estimates of Variation with Respect to a Set and Applications to Optimization Problems
GNECCO, G ; SANGUINETI, M
Journal of optimization theory and applications. 145(1):53-75

Control theory, operatio... Automatique, recherche o... Computer science Informatique Sciences exactes et tech... Exact sciences and techn... …
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125

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126

Teaching Functional Patterns through Robotic Applications
Boender, J. ; Currie, E. ; Loomes, M. ; et al.
EPTCS 230, 2016, pp. 17-29

Computer Science - Compu... Computer Science - Progr...
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127

Logic programs with functions and default values
CABALAR, Pedro ; LORENZO, David
Logics in artificial intelligence (Lisbon, 27-30 September 2004)Lecture notes in computer science. :294-306

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128

Predicting optimal deep brain stimulation parameters for Parkinson's disease using functional MRI and machine learning
Alexandre Boutet ; Radhika Madhavan ; Gavin J. B. Elias ; et al.
Nature, Nature Communications. 12(1):1-13

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129

Go! for multi-threaded deliberative agents
CLARK, Keith L ; MCCABE, Frank G
DALT 2003 : declarative agent languages and technologies (Melbourne, 15 July 2003, revised selected and invited papers)Lecture notes in computer science. :54-75

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130

Automatically parallelizing batch inference on deep neural networks using Fiats and Fortran 2023 `do concurrent`
Rouson, Damian ; Bai, Zhe ; Bonachea, Dan ; et al.

Atmospheric Sciences Deep learning Fortran class-fortran (c-lbnl-la... Artificial Intelligence... 46 Information and compu...
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131

VML: A View Modeling Language for computational knowledge discovery
BANNAI, Hideo ; TAMADA, Yoshinori ; MARUYAMA, Osamu ; et al.
DS 2001 : discovery science (Washington DC, 25-28 November 2001)Lecture notes in computer science. :30-44

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132

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133

Improved tupling for optimizing multi-paradigm declarative programs
GONZALEZ, Soledad ; MORENO, Ginés
Advances in artificial intelligence : IBERAMIA 2004 (Puebla, 22-26 November 2004)Lecture notes in computer science. :419-429

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134

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135

Automatic optimization of multi-paradigm declarative programs
MORENO, Ginés
IBERAMIA 2002 : advances in artificial intelligence (Seville, 12-15 November 2002)Lecture notes in computer science. :131-140

Control theory, operatio... Automatique, recherche o... Computer science Informatique Sciences exactes et tech... Exact sciences and techn... …
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136

Central limit theorems for vector-valued composite functionals with smoothing and applications
Huihui Chen ; Darinka Dentcheva ; Yang Lin ; et al.
Annals of the Institute of Statistical Mathematics. 77(5):821-852

Coherent measure of risk...
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137

Introduction to Classical Density Functional Theory by a Computational Experiment
Jeanmairet, Guillaume ; Levy, Nicolas ; Levesque, Maximilien ; et al.
Journal of Chemical Education. 91(12):2112-2115

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138

Using schedule-correlated stimuli during functional communication training to promote the rapid transfer of treatment effects.
Greer, Brian D. ; Fisher, Wayne W. ; Briggs, Adam M. ; et al.
Behavioral Development Bulletin

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139

A general framework for R-unification problems
LIMET, S ; SAUBION, F
Principles of declarative programming (Pisa, 16-18 September 1998)Lecture notes in computer science. :266-281

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140

Hey Pentti, We Did It Again!: Differentiable vector-symbolic types that prove polynomial termination
Tomkins-Flanagan, Eilene ; Hanley, Connor ; Kelly, Mary A.
Tomkins Flanagan, E., Hanley, C., & Kelly, M. A. (2025, July). Paper presented at MathPsych / ICCM 2025. Via mathpsych.org/presentation/1997

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