📢Come to our NeurIPS session on Wednesday (4:30pm–6pm PT)!
We show score-based generative models can be trained as a continuous normalizing flow (ScoreFlow) efficiently with a variational objective, achieving outstanding likelihood values that match best autoregressive models.
Attending #NeurIPS2022? Make sure to add our NeurIPS workshop on score-based methods (https://t.co/gRoqSbmmgd) to your schedule! Our amazing panelists will be answering your questions—submit them now via this Google form: https://t.co/vOlzNvk58s.
Zoom in on the Andromeda Galaxy with Hubble. What looks like a smudge of light to the unaided eye is actually a vast galaxy containing an estimated 1 trillion stars.
Credit: ESA/Hubble & NASA
Full HD version on Youtube: https://t.co/uE6XQiyJ5e
7. NLP with Deep Learning by Stanford
This course will enable you to build complex NLP solutions (in Pytorch) for a variety of NLP tasks.
👉 https://t.co/79h1qtwBzP
We’ve posted a new paper on how learning a new behavior leaves a “memory trace” of the learned behavior in neural population activity:
https://t.co/3s40iN8V1J
"Learning alters neural activity to simultaneously support memory and action"
Excited to share a new preprint, led by Darby Losey, with myself, Emily Oby, Aaron Batista, Byron Yu, Steve Chase, and team. 🧵
https://t.co/xMsBS5hOuP
I don’t love crypto VCs but Su and Kyle building up a multi-billion dollar fund from their closet is nothing short of remarkable. Su’s insight on podcasts have been some of the most valuable content I’ve found in the entire space. Hope they come out the other side of this. 🫡
TxnLab is pleased to announce that we are developing an #Algorand native naming service for .algo names. Our platform will enable users to send & receive $ALGO using a unique name that is easy to type and remember.
🧵👇
Excited to share we (@yulikeneuro@aaronbatista and others) have a perspectives paper on learning in neural population activity out now!
"How learning unfolds in the brain: toward an optimization view"
📎 https://t.co/eRSEyg86TW
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Finished the 2nd Edition of "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" with Nathan Kutz today for Cambridge.
Now w Python + MATLAB, extensive HW, and YouTube videos for all sections! (Code in Julia and R soon)
https://t.co/m3S9fwy4y4