TCN Paper Ideas: Difference between revisions

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(Created page with "Post ideas about interesting papers to read below. I ==Spring 2016== Ideas from the Nando Fretas AMA: * Teaching machines to read and comprehend, http://arxiv.org/abs/1506....")
 
 
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Ideas from the Nando Fretas AMA:
Ideas from the Nando Fretas AMA:


* Teaching machines to read and comprehend, http://arxiv.org/abs/1506.03340[1] (can someone help me with how to add links to this properly???)
* Teaching machines to read and comprehend, http://arxiv.org/abs/1506.03340[1]  
* Spatial transformer networks, http://arxiv.org/abs/1506.02025[2]
* Pointer networks, http://arxiv.org/abs/1506.03134[3]
* Pointer networks, http://arxiv.org/abs/1506.03134[3]
* Neural GPUs learn algorithms, http://arxiv.org/abs/1511.08228[4]
* Neural GPUs learn algorithms, http://arxiv.org/abs/1511.08228[4]
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* Hippocampal place cells construct reward related sequences through unexplored space
* Hippocampal place cells construct reward related sequences through unexplored space
* Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images, http://arxiv.org/abs/1506.07365[11]
* Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images, http://arxiv.org/abs/1506.07365[11]
Vijay Mohan a post-doc from UNC generously put together this reading list for me on computational models of neuromodulators. Haven't read them all yet, but looks like some good stuff and might be a good way to add some neuroscience to the mix to counterbalance all the deep learning.
* [http://www.ncbi.nlm.nih.gov/pubmed/19346478 Learning reward timing in cortex through reward dependent expression of synaptic plasticity]
* [http://www.cell.com/cell/abstract/S0092-8674%2815%2900973-3 Central Cholinergic Neurons Are Rapidly Recruited by Reinforcement Feedback]
* [http://www.sciencedirect.com/science/article/pii/S0960982215004790 Selective Activation of a Putative Reinforcement Signal Conditions Cued Interval Timing in Primary Visual Cortex]
* [http://www.sciencedirect.com/science/article/pii/S0896627305003624 Uncertainty, Neuromodulation, and Attention]
* [http://www.gatsby.ucl.ac.uk/~dayan/papers/25lessons.pdf Twenty-Five Lessons from Computational Neuromodulation]

Latest revision as of 20:54, 8 January 2016

Post ideas about interesting papers to read below. I

Spring 2016

Ideas from the Nando Fretas AMA:

Vijay Mohan a post-doc from UNC generously put together this reading list for me on computational models of neuromodulators. Haven't read them all yet, but looks like some good stuff and might be a good way to add some neuroscience to the mix to counterbalance all the deep learning.