FitnessSyncer joins your health and fitness clouds into one Dashboard and Stream. Supporting over 40 health and fitness providers, including Fitbit, Garmin Connect, Samsung Health, Microsoft HealthVault™, RunKeeper, and more!
Engineer friends often ask me: Graph Deep Learning sounds great, but are there any big commercial success stories? Is it being deployed in practical applications? Besides the obvious ones–recommendation systems at Pinterest, Alibaba and Twitter–a slightly nuanced success story is the Transformer architecture, which has taken the NLP industry by storm. Through this post, I want to establish links between Graph Neural Networks (GNNs) and Transformers. I’ll talk about the intuitions behind model architectures in the NLP and GNN communities, make connections using equations and figures, and discuss how we could work together to drive progress.
Das Coronavirus breitet sich auf der Welt aus. Täglich steigt die Zahl der Infektionen – weltweit, in Europa und in den Bundesländern in Deutschland. Schauen Sie sich hier die Echtzeit-Karte an.
With everything that’s happening about the Coronavirus, it might be very hard to make a decision of what to do today. Should you wait for more information? Do something today? What? Here’s what I’m…
Bayesian Methods for Hackers : An intro to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view.
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome - GitHub - jerryji1993/DNABERT: DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
Diffusion Bee is the easiest way to run Stable Diffusion locally on your M1 Mac. Comes with a one-click installer. No dependencies or technical knowledge needed. - GitHub - divamgupta/diffusionbee-stable-diffusion-ui: Diffusion Bee is the easiest way to run Stable Diffusion locally on your M1 Mac. Comes with a one-click installer. No dependencies or technical knowledge needed.
The Hiveeyes Project is developing a flexible beehive monitoring infrastructure platform and toolkit based on affordable hardware, wireless telemetry and modern software. Open source, open hardware and a friendly community.
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S. Wankerl, A. Dulny, G. Götz, and A. Hotho. 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), page 1681-1687. (December 2021)