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Artificial Intelligence Networks Towards Learning Without Forgetting

Kreiman et al. | Oct 26, 2018

Artificial Intelligence Networks Towards Learning Without Forgetting

In their paper, Kreiman et al. examined what it takes for an artificial neural network to be able to perform well on a new task without forgetting its previous knowledge. By comparing methods that stop task forgetting, they found that longer training times and maintenance of the most important connections in a particular task while training on a new one helped the neural network maintain its performance on both tasks. The authors hope that this proof-of-principle research will someday contribute to artificial intelligence that better mimics natural human intelligence.

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Simulations of Cheetah Roaming Demonstrate the Effect of Safety Corridors on Genetic Diversity and Human-Cheetah Conflict

Acton et al. | Apr 02, 2018

Simulations of Cheetah Roaming Demonstrate the Effect of Safety Corridors on Genetic Diversity and Human-Cheetah Conflict

Ecological corridors are geographic features designated to allow the movement of wildlife populations between habitats that have been fragmented by human landscapes. Corridors can be a pivotal aspect in wildlife conservation because they preserve a suitable habitat for isolated populations to live and intermingle. Here, two students simulate the effect of introducing a safety corridor for cheetahs, based on real tracking data on cheetahs in Namibia.

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Investigating Lymphocytic Involvement in Minimal Change Nephrotic Syndrome

Muncan et al. | Jan 27, 2016

Investigating Lymphocytic Involvement in Minimal Change Nephrotic Syndrome

Minimal Change Disease (MCD) is a degenerative kidney disease. Researchers know very little about the cause of this disorder, however some research has suggested that T lymphocytes may be involved. In this study, the authors measure CD4 and CD8 T cell subpopulations in patients with MCD to investigate whether irregular T lymphocyte populations may be involved in MCD pathogenesis.

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