#csharp#2d#avaloniaui#csharp#dotnet_core#dotnetcore#editor#game_development#graphics#graphics_editor#linux_desktop#painting#pixel_art#pixi#procedural_drawing#procedural_generation#raster_graphics#sprites#tabs#vector_graphics
PixiEditor is a free, easy-to-use 2D graphics editor that combines pixel art, painting, and vector tools all in one program. You can create game sprites, animations, logos, and edit images with a simple interface. It supports mixing vector and raster graphics on the same canvas and lets you export to many formats like PNG, SVG, GIF, and MP4. The powerful Node Graph system allows you to create complex, non-destructive effects and animations. It also has a timeline for frame-by-frame animation and autosaves your work to prevent loss. This makes it a versatile tool for artists and game developers.
https://github.com/PixiEditor/PixiEditor
#DL
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Zeus New Pytorch Ecosystem Tool
Zeus is an open source toolkit for measuring and optimizing power consumption of deep learning workloads.
🖥Github
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Main channel: @repo_science
Coupons: @freecoupons_reposcience
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#dl
Park, Chanwook, Sourav Saha, Jiachen Guo, Hantao Zhang, Xiaoyu Xie, Miguel A. Bessa, Dong Qian, et al. 2025. “Unifying Machine Learning and Interpolation Theory via Interpolating Neural Networks.” Nature Communications 16 (1): 1–12.
https://www.nature.com/articles/s41467-025-63790-8
#dl
A few cool ideas in this model.
Introducing Gemma 3n: The developer guide - Google Developers Blog
https://developers.googleblog.com/en/introducing-gemma-3n-developer-guide/
#dl
There is this new lib called scale. One could compile CUDA code to use it on AMD GPU.
https://docs.scale-lang.com/manual/how-to-use/
I don't know who is more pissed off, NVidia or AMD.
#dl
This repo is really nice.
yuanchenyang/smalldiffusion: Simple and readable code for training and sampling from diffusion models
https://github.com/yuanchenyang/smalldiffusion
#dl
Google & USC benchmarked a prompt based forecasting method, and the results are amazing.
Cao D, Jia F, Arik SO, Pfister T, Zheng Y, Ye W, et al. TEMPO: Prompt-based Generative Pre-trained Transformer for time series forecasting. arXiv [cs.LG]. 2023. Available: http://arxiv.org/abs/2310.04948