1,779,462 research outputs found
MALA
No full textFeatures
Parallel preprocessing, network training and model inference
Distributed hyperparameter optimization (Optuna) and distributed training-free network architecture optimization (NASWOT)
Reproducibility through single Parameters object, easy interface to JSON for automated sweeps
Internal caching system for intermediate quantities (e.g. DOS, density, band energy) for improved performance
Modular design
OF-DFT-MD interface to create initial configurations for ML based sampling
Change notes:
MALA now operates internally in Angstrom consistently
Volumetric data that has been created with MALA v1.0.0 can still be used, but unit conversion has to be added to the scripts in question
Implemented caching functionality
The old post-processing API is still fully functional, but will not use the caching functions; instead, MALA now has a more streamlined API tying calculators to data
More flexible data conversion methods
Improved Optuna distribution scheme
Implemented parallel total energy inference
Reduced import time for MALA module
Several smaller bugfixesIf you use this software, please cite it using these metadata
Interview with Mala Singh
No full textMala Singh talked to the GUNI about the present and the future of higher education in Africa, which she thinks can help overcome ethnic conflicts by strengthening a common African identity
The executive director of the Higher Education Quality Committee (HEQC) of the Council on Higher Education, Mala Singh, believes that an African higher education area is still in its infancy and that governments need to implement effective measures to assure quality and recognize qualifications across the continent. Ms. Singh also talked about how higher education in Africa can contribute to social goals and discussed the need to create more stable social and political environments in order to fight brain drain. Ms. Singh presented the paper ‘The Governance of Accreditation’ at the 3rd International Barcelona Conference on Higher Education: Accreditation for Quality Assurance: What is at Stake
Interview with Mala Singh
No full textMala Singh talked to the GUNI about the present and the future of higher education in Africa, which she thinks can help overcome ethnic conflicts by strengthening a common African identity
The executive director of the Higher Education Quality Committee (HEQC) of the Council on Higher Education, Mala Singh, believes that an African higher education area is still in its infancy and that governments need to implement effective measures to assure quality and recognize qualifications across the continent. Ms. Singh also talked about how higher education in Africa can contribute to social goals and discussed the need to create more stable social and political environments in order to fight brain drain. Ms. Singh presented the paper ‘The Governance of Accreditation’ at the 3rd International Barcelona Conference on Higher Education: Accreditation for Quality Assurance: What is at Stake
Test data for MALA
No full textThis repository contains data to test, develop and debug MALA and MALA based runscripts. If you plan to do machine-learning tests ("Does this network implementation work? Is this new data loading strategy working?"), this is the right data to test with. It is NOT production level data
Test data for MALA
No full textThis repository contains data to test, develop and debug MALA and MALA based runscripts. If you plan to do machine-learning tests ("Does this network implementation work? Is this new data loading strategy working?"), this is the right data to test with. It is NOT production level data
Test data for MALA
No full textThis repository contains data to test, develop and debug MALA and MALA based runscripts. If you plan to do machine-learning tests ("Does this network implementation work? Is this new data loading strategy working?"), this is the right data to test with. It is NOT production level data
Test data for MALA
No full textThis repository contains data to test, develop and debug MALA and MALA based runscripts. If you plan to do machine-learning tests ("Does this network implementation work? Is this new data loading strategy working?"), this is the right data to test with. It is NOT production level data
Test data for MALA
No full textThis repository contains data to test, develop and debug MALA and MALA based runscripts. If you plan to do machine-learning tests ("Does this network implementation work? Is this new data loading strategy working?"), this is the right data to test with. It is NOT production level data
«Mala onda», «lata» e «ironía» en Mala onda de Alberto Fuguet
No full textThis article discusses Mala onda, the Bildungsroman published by Alberto Fuguet at the start of the Chilean postdictaorial transition which has received reproaches from the right and criticism from the left. The interpretation offers three basic solutions: unacceptance of the the given (Manuel Rojas, Hijo de ladrón), negotiation with the given (Alberto Blest Gana, Martín Rivas; Antonio Skármeta, No pasó nada), and finally acceptation of the given which is inevitable. The novel Mala onda is an example of the last option, however, the ironic tone of the narrative subverts and disarms this option.Este trabajo se ocupa de Mala onda, la Bildungsroman que Alberto Fuguet publicó en los inicios de la transición postdictatorial chilena y que ha merecido los reproches de la derecha y la izquierda críticas. La lectura que aquí se ofrece parte de la elección del autor entre las tres soluciones básicas de que dispone este tipo de relatos para resolver la encrucijada del crecimiento adolescente, y que son la de la no aceptación de lo dado (Manuel Rojas, Hijo de ladrón), la de la negociación con lo dado (Alberto Blest Gana, Martín Rivas; Antonio Skármeta, No pasó nada) y la de la aceptación de lo dado por las buenas o por las malas. Aunque es cierto que la ironía narrativa va a desarmarla en el relato, el protagonista de Mala onda va a optar por esta última opción
Test data for MALA
No full textThis repository contains data to test, develop and debug MALA and MALA based runscripts. If you plan to do machine-learning tests ("Does this network implementation work? Is this new data loading strategy working?"), this is the right data to test with. It is NOT production level data
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