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24/ Terraforms by Mathcastles The "hypercastle" is a dynamically computed, evolving, reinterpretable, non-visual 3D structure of thousands of parcels of unicode land art. Parcels can be "terraformed" via contract functions, shaping the 32x32 grid (visuals: Hypercastle Explorers)

16,918 просмотров • 1 год назад •via X (Twitter)

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INTRODUCING OCBTW: THE FIRST PANDA-BACKED ASSET A FIRST-OF-ITS-KIND 2-WAY NFT NFT SWAP We just deployed a smart contract on Bitcoin that allows you to mint "OCBTW", a limited edition generative art collection by tclow.sats, solely by swapping an Alkane Pandas ⬢ OCBTW has a supply of 200 unique pieces and is inspired by oylwallet's signature hexagon logo that defines all native Alkane assets (e.g., $DIESEL). It is 100% on-chain generative art using three.js code via HTML ⬢ OCBTW can only be minted by swapping a Panda using the 2:70104 smart contract. After 200 swaps have been completed, on a first-come-first-served basis, the mint will conclude. However, OCBTW can be swapped back to a Panda at any time, freeing up supply for another Panda holder to collect a OCBTW piece from the contract. ⬢ OCBTW is thus backed entirely by Pandas, meaning each piece will never be worth less than a Panda. This is the first time on Bitcoin that an NFT is minted with another NFT. This may be the first time this has ever been done on any chain. ⬢ OCBTW also effectively locks up up to 200 Pandas for perpetuity. Just like AP-69, this swap contract has no withdrawal function. The only way to get Pandas out of the contract is to swap your OCBTW back to a Panda. This operates on a last-in, first-out (LIFO) basis. ⬢ OCBTW can be minted by calling the 2:70104 contract using opcode 42 and including a Panda in the transaction, either by using or You can only mint 1 OCBTW per transaction. Rarity of Pandas has no effect on what OCBTW mint you will receive. ⬢ OCBTW can be viewed natively in browser on iDclub 💥 Building Alkanes at the following link: Please be patient after minting for their indexer to update after blocks clear. Please also note that the Ordiscan Alkanes indexer is currently down. ⬢ OCBTW is purely art. Art on Bitcoin. Forever.

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NeuRBF: A Neural Fields Representation with Adaptive Radial Basis Functions paper page: present a novel type of neural fields that uses general radial bases for signal representation. State-of-the-art neural fields typically rely on grid-based representations for storing local neural features and N-dimensional linear kernels for interpolating features at continuous query points. The spatial positions of their neural features are fixed on grid nodes and cannot well adapt to target signals. Our method instead builds upon general radial bases with flexible kernel position and shape, which have higher spatial adaptivity and can more closely fit target signals. To further improve the channel-wise capacity of radial basis functions, we propose to compose them with multi-frequency sinusoid functions. This technique extends a radial basis to multiple Fourier radial bases of different frequency bands without requiring extra parameters, facilitating the representation of details. Moreover, by marrying adaptive radial bases with grid-based ones, our hybrid combination inherits both adaptivity and interpolation smoothness. We carefully designed weighting schemes to let radial bases adapt to different types of signals effectively. Our experiments on 2D image and 3D signed distance field representation demonstrate the higher accuracy and compactness of our method than prior arts. When applied to neural radiance field reconstruction, our method achieves state-of-the-art rendering quality, with small model size and comparable training speed.

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