Offshore
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Claire Silver 🌸
RT @phomo_eth: dreaming of securing the bag so i can kick off the auction for this 1/1
blows my mind that it’s still available
‘Pieces’ x @ClaireSilver12 🌸💎 https://t.co/wja6hVa5Le
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RT @phomo_eth: dreaming of securing the bag so i can kick off the auction for this 1/1
blows my mind that it’s still available
‘Pieces’ x @ClaireSilver12 🌸💎 https://t.co/wja6hVa5Le
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Offshore
Photo
UnknownCollector - NG Drop soon
RT @ArtM0o: Looking to make my first sale of 2023, so, Here are some of my available pieces on @foundation .
I Fell Apart When You Left - 0.2 ETH
Host - 0.1 ETH
Flourish - 0.22 ETH
Separation Anxiety - 0.1 ETH.
Please share and retweet if you come across this tweet ❤
Link below. https://t.co/RbfD5YnrR2
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RT @ArtM0o: Looking to make my first sale of 2023, so, Here are some of my available pieces on @foundation .
I Fell Apart When You Left - 0.2 ETH
Host - 0.1 ETH
Flourish - 0.22 ETH
Separation Anxiety - 0.1 ETH.
Please share and retweet if you come across this tweet ❤
Link below. https://t.co/RbfD5YnrR2
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Offshore
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AK
Accelerating Guided Diffusion Sampling with Splitting Numerical Methods
abs: https://t.co/6HWSQ1PnlJ
github: https://t.co/PlTuQpDIoa https://t.co/CAl2HFIuaG
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Accelerating Guided Diffusion Sampling with Splitting Numerical Methods
abs: https://t.co/6HWSQ1PnlJ
github: https://t.co/PlTuQpDIoa https://t.co/CAl2HFIuaG
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Offshore
Photo
AK
PLay: Parametrically Conditioned Layout Generation using Latent Diffusion
abs: https://t.co/x5S2KXi6WH https://t.co/gbYNDZnJb5
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PLay: Parametrically Conditioned Layout Generation using Latent Diffusion
abs: https://t.co/x5S2KXi6WH https://t.co/gbYNDZnJb5
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Offshore
GIF
AK
3DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion Models
abs: https://t.co/Cg7BxuI6sn
project page: https://t.co/QBQUH9p2VZ https://t.co/NaLv2Cex9N
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3DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion Models
abs: https://t.co/Cg7BxuI6sn
project page: https://t.co/QBQUH9p2VZ https://t.co/NaLv2Cex9N
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Offshore
Video
Aran Komatsuzaki
Moûsai: Text-to-Music Generation with Long-Context Latent Diffusion
Develops a cascading latent diffusion approach that can generate multiple minutes of high-quality stereo music at 48kHz from textual descriptions.
abs: https://t.co/UpoywkQI05
repo: https://t.co/XqHCYSyg2l https://t.co/EiPn9luH6f
tweet
Moûsai: Text-to-Music Generation with Long-Context Latent Diffusion
Develops a cascading latent diffusion approach that can generate multiple minutes of high-quality stereo music at 48kHz from textual descriptions.
abs: https://t.co/UpoywkQI05
repo: https://t.co/XqHCYSyg2l https://t.co/EiPn9luH6f
tweet
Offshore
Photo
Aran Komatsuzaki
Leveraging the Third Dimension in Contrastive Learning
Leveraging the additional depth channel dimension of BYOL leads to an increase in downstream classification accuracy from 85.3% to 88.0% on ImageNette and 84.1% to 87.0% on ImageNet-C.
https://t.co/DleM5sZ0lY https://t.co/xPXSMkyOeT
tweet
Leveraging the Third Dimension in Contrastive Learning
Leveraging the additional depth channel dimension of BYOL leads to an increase in downstream classification accuracy from 85.3% to 88.0% on ImageNette and 84.1% to 87.0% on ImageNet-C.
https://t.co/DleM5sZ0lY https://t.co/xPXSMkyOeT
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Offshore
Photo
Aran Komatsuzaki
SWARM Parallelism: Training Large Models Can Be Surprisingly Communication-Efficient
Shows that it is possible to train a billion-scale LM on preemptible servers with low-power GPUs and low network bandwidth while achieving high training throughput.
https://t.co/3Sx9Klc4i2 https://t.co/Yrz9t8o5HK
tweet
SWARM Parallelism: Training Large Models Can Be Surprisingly Communication-Efficient
Shows that it is possible to train a billion-scale LM on preemptible servers with low-power GPUs and low network bandwidth while achieving high training throughput.
https://t.co/3Sx9Klc4i2 https://t.co/Yrz9t8o5HK
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