~hackernoon | Bookmarks (2011)
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POWER LEADER: Anvl's Zach Taylor on the Connected Worker Platform for Safety and Productivity
Anvl’s AI Connected Worker Platform is the sole digital layer for industrial enterprises to digitally transform...
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HackerNoon's Emoji Credibility Indicators are Live on GitHub and Figma!
Emoji Credibility Indicators by HackerNoon are now live on GitHub and Figma!!! Our open-source pixelated emoji...
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The Rise of NFTs: The Future of Digital Ownership
NFTs are unique digital assets that gained popularity in 2021. They offer proof of ownership for...
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The React AI Library Upgrade You May Have Been Looking For
Gitroom is an open-sourced tool that lets you schedule posts on multiple social media platforms and...
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Code Smell 247 - Javascript Function Naming
Some names in immature languages break the [bijection] principle. Avoid ambiguous or bad names. Wrap with...
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Meet Neurahub - The Perfect Coding Buddy to Help You Learn and Create
Neurahub is an up-and-coming platform allowing users to harness the limitless power of artificial intelligence to...
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Nimiq Pay: Connecting Cryptocurrency with Daily Payments
Nimiq Pay is a self-custodial crypto payments app that doesn't require installation. Nimiq's main objective is...
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ICP Unveils Game-Changing Integration to Transform Bitcoin into Layer Zero
The Internet Computer Protocol (ICP) has introduced threshold-Schnorr signatures, a significant update poised to position ICP...
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HyperTransformer: G Additional Tables and Figures
In this paper we propose a new few-shot learning approach that allows us to decouple the...
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HyperTransformer: F Visualization of The Generated CNN Weights
In this paper we propose a new few-shot learning approach that allows us to decouple the...
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HyperTransformer: C Additional Supervised Experiments
In this paper we propose a new few-shot learning approach that allows us to decouple the...
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HyperTransformer: A Example of a Self-Attention Mechanism For Supervised Learning
In this paper we propose a new few-shot learning approach that allows us to decouple the...
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HyperTransformer: Conclusion and References
In this paper we propose a new few-shot learning approach that allows us to decouple the...
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HyperTransformer: B Model Parameters
In this paper we propose a new few-shot learning approach that allows us to decouple the...
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HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning: Experiments
In this paper we propose a new few-shot learning approach that allows us to decouple the...
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Efficient Neural Network Approaches for Conditional Optimal Transport: Discussion and Reference
This paper presents two neural network approaches that approximate the solutions of static and dynamic conditional...
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Efficient Neural Network Approaches for Conditional Optimal Transport: Numerical Experiments
This paper presents two neural network approaches that approximate the solutions of static and dynamic conditional...
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Efficient Neural Network Approaches: Implementation and Experimental Setup
This paper presents two neural network approaches that approximate the solutions of static and dynamic conditional...
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Efficient Neural Network Approaches: Partially Convex Potential Maps (PCP-Map) for Conditional OT
This paper presents two neural network approaches that approximate the solutions of static and dynamic conditional...
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Efficient Neural Network Approaches for Conditional Optimal Transport:Conditional OT flow (COT-Flow)
This paper presents two neural network approaches that approximate the solutions of static and dynamic conditional...
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Efficient Neural Network Approaches for Conditional Optimal Transport: Background and Related Work
This paper presents two neural network approaches that approximate the solutions of static and dynamic conditional...
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Efficient Neural Network Approaches for Conditional Optimal Transport: Abstract & Introduction
This paper presents two neural network approaches that approximate the solutions of static and dynamic conditional...
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Using Autodiff to Estimate Posterior Moments, Marginals and Samples: Experimental Datasets and Model
Importance weighting allows us to reweight samples drawn from a proposal in order to compute expectations...