Artificial neural networks
Recent articles
This paper changed my life: Appreciating John Hopfield’s brilliant neural network
In a 1982 paper, the Nobel laureate created his namesake recurrent neural network—work that taught Maria Geffen to always ground research questions in biology.
This paper changed my life: Appreciating John Hopfield’s brilliant neural network
In a 1982 paper, the Nobel laureate created his namesake recurrent neural network—work that taught Maria Geffen to always ground research questions in biology.
Kim Stachenfeld on the dance between neuroscience and artificial intelligence
As a researcher at both Google DeepMind and Columbia University, Stachenfeld offers cross-disciplinary insight into how to understand the brain.
Kim Stachenfeld on the dance between neuroscience and artificial intelligence
As a researcher at both Google DeepMind and Columbia University, Stachenfeld offers cross-disciplinary insight into how to understand the brain.
Explore more from The Transmitter
Fruit flies use memory to track odors
When flies encounter a tasty smell, they stroll in and out of the odor plume—a process that depends on encoding a memory of the angle needed to travel back to the plume, according to a new study.
Fruit flies use memory to track odors
When flies encounter a tasty smell, they stroll in and out of the odor plume—a process that depends on encoding a memory of the angle needed to travel back to the plume, according to a new study.
New methods to contextualize autism-linked genes, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 7 September.
New methods to contextualize autism-linked genes, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 7 September.
Dimensionality—neuroscience’s red herring?
Placing too much emphasis on a specific interpretation of dimensionality, or treating it as an end-all quantification of some aspect of neural computation, may hinder progress in understanding the brain.
Dimensionality—neuroscience’s red herring?
Placing too much emphasis on a specific interpretation of dimensionality, or treating it as an end-all quantification of some aspect of neural computation, may hinder progress in understanding the brain.