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“Taking inspiration from distributional reinforcement learning in artificial intelligence, the researchers analysed neuronal recordings from the mouse midbrain and found that instead of the brain representing the future as a single mean, it uses a probability...” lovely work!https://twitter.com/nature/status/1222604066796331008 …
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Peng Liu proslijedio/la je Tweet
This looks pretty interesting Neurons in Visual Cortex are Driven by Feedback Projections when their Feedforward Sensory Input is Missing https://www.biorxiv.org/content/10.1101/2020.01.24.919142v1 …pic.twitter.com/8p59hN9h8O
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Recurrent feedback can improve deep neural network and our brains to better identify objects from DiCarlo labhttps://rocmind.com/2020/01/26/recurrent-feedback-can-improve-deep-neural-network-and-our-brains-to-better-identify-objects-from-dicarlo-lab/ …
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Peng Liu proslijedio/la je Tweet
Given the smoothness of videos, can we learn models more efficiently than with
#backprop? We present Sideways - a step towards a high-throughput, approximate backprop that considers the one-way direction of time and pipelines forward and backward passes. https://arxiv.org/pdf/2001.06232.pdf …pic.twitter.com/evbwULE0s2Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Peng Liu proslijedio/la je Tweet
I am frequently asked by students about transition into "independence in science", the ability "to do things alone". I want to challenge that concept and argue that framing training as path towards "independence" is confusing for many. True "independence"="interdependence"(1/n)
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Peng Liu proslijedio/la je Tweet
A fascinating new Nature paper from
@DeepMindAI hypothesizes (and shows supporting data!) about how state of the art reinforcement-learning algorithms may explain how dopamine works in our brains.https://www.technologyreview.com/s/615054/deepmind-ai-reiforcement-learning-reveals-dopamine-neurons-in-brain/ …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Peng Liu proslijedio/la je Tweet
University courses at bachelor degree level seriously need to address their lack of coding courses. These should be mandatory for all sciences, especially social sciences, and part of every research methods course. It should be integral to the teaching of statistics.
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The intuitive interactions between brain and physics! Interesting!
#naturereview#physics#brainhttps://twitter.com/leafs_s/status/1215554689179062272 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Peng Liu proslijedio/la je Tweet
A prospective clinical trial of
#AI to determine intraoperative#cancer in near real time using label-free imaging: impressive rapid, accurate results by@umichneuro@ToddCHollon@DanOrringerMD & collaborators@NatureMedicine https://www.nature.com/articles/s41591-019-0715-9 …pic.twitter.com/3V962i5aVO
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Peng Liu proslijedio/la je Tweet
Brains are amazing. Our lab demonstrates that single human layer 2/3 neurons can compute the XOR operation. Never seen before in any neuron in any other species. Out now in
@sciencemagazine. Congrats Albert, Tim@mattlark@YiotaPoirazi & COhttps://science.sciencemag.org/content/367/6473/83 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Peng Liu proslijedio/la je Tweet
The latest from Martin Haesemeyer, comparing artificial and biological neural networks - now published in Neuron! We find striking parallels and use the ANN to make testable predictions about the biology. https://www.cell.com/neuron/fulltext/S0896-6273(19)30601-4 …pic.twitter.com/CFcraNrDeU
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Peng Liu proslijedio/la je Tweet
While Bayesian models provide good accounts of perceptual decisions, it is unclear how their components are represented in the brain. Here, the authors show that uncertainty decoded from visual cortex helps predict behavior. https://go.nature.com/2EOvPGO pic.twitter.com/p9lgLhz01q
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Peng Liu proslijedio/la je Tweet
1/ New tweeprint from my lab! This one is work done by the amazing
@guerguiev, and was inspired by the work of@benlansdell and@KordingLab (who was also a collaborator in this project). https://arxiv.org/abs/1910.01689Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Peng Liu proslijedio/la je Tweet
My talk at
#GTC19 China on latest works on generative models that I have been involved in both at@NvidiaAI and@Caltech Some topics: competitive optimization, disentanglement in StyleGAN, flow-based models for turbulence modeling, CNN-feedback networks https://caltech.box.com/s/3aff4e5qtk9e0rizr714xes8ryga2ov0 …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Peng Liu proslijedio/la je Tweet
Amazing new
@NatureNeuro study from@LabPapaleo led by@DiegoScheggia &@FrancescaManago on SOM interneurons being critical to emotion discrimination! The@Inscopix nVistaᵀᴹ + nVokeᵀᴹ are proud to be part of it.
Read more- https://hubs.ly/H0mjL1T0 . @UniPadova#InscopixNetworkHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Peng Liu proslijedio/la je Tweet
On some level, I would have been shocked if this didn't exist in the brain, but cool to see it demonstrated! Invariant representations of mass in the human brain:https://doi.org/10.7554/eLife.46619 …
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nice! I've been thinking of this for a while. Will be much helpful https://twitter.com/DeepMind/status/1206536220085501955 …pic.twitter.com/Ck3FIPQbpW
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Peng Liu proslijedio/la je Tweet
What does it mean to understand language? We argue that human-like understanding requires complementary memory systems and rich representations of situations. A roadmap for extending ML models toward human-level language understanding: https://arxiv.org/abs/1912.05877 pic.twitter.com/eKBOekfmgj
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the points" Raising research quality will require collective action. Institutions must act together to reform research culture. If we want researchers to work well in large collaborations, we need to train them in communication skills and collective self-scrutiny"
@MarcusMunafohttps://twitter.com/NatureNews/status/1205559272077168642 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Peng Liu proslijedio/la je Tweet
I have a new paper with Dan Rubin &
@kendmil on biorxiv! "A simple circuit model of visual cortex explains neural and behavioral aspects of attention" https://www.biorxiv.org/content/10.1101/2019.12.13.875534v1 … We replicated findings (and figures) from several experimental papers, all using the same basic model!Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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