[upstream-sync] README.md from ai-boost/awesome-ai-for-science@2ac4cc1f [catalogue]

2026-08-25 16:52:47 +00:00
1 changed files with 5 additions and 3 deletions
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 title: "Readme"
 task: ""
 lineage_type: import
-upstream_source: https://github.com/ai-boost/awesome-ai-for-science/blob/e0557705/README.md
-upstream_sha: e0557705
-imported_at: 2026-08-23
+upstream_source: https://github.com/ai-boost/awesome-ai-for-science/blob/2ac4cc1f/README.md
+upstream_sha: 2ac4cc1f
+imported_at: 2026-08-25
 prompt_class: catalogue
 upstream_changes: accepted
 author: upstream
@@ -237,6 +237,7 @@ validated: false
 - [Obsidian Smart Connections](https://github.com/brianpetro/obsidian-smart-connections) - AI-powered note linking and research graph navigation
 - [Research Rabbit](https://www.researchrabbit.ai/) - AI-powered literature discovery and research network mapping
 - [SciWrite](https://github.com/labarba/sciwrite) - Agent skill for AI-assisted scientific manuscript writing review distilled from Stanford's *Writing in the Sciences* course, performing five sequential editorial audit passes on clarity, voice, structure, consistency, and integrity (2026)
+- [PaperSpine](https://github.com/WUBING2023/PaperSpine) - Motivation-driven academic writing system for Claude Code, Codex, OpenClaw, and Hermes CLI that learns from strong papers, builds evidence-aware central-argument blueprints, and rewrites manuscripts with revision matrices and LaTeX-safe audits (4.9K+ stars, MIT License, 2026)
 - [Claude Prism](https://github.com/delibae/claude-prism) - Offline-first scientific writing workspace powered by Claude, integrating LaTeX, Python, and 100+ scientific skills with local execution, Zotero integration, and privacy-focused design (2026)

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 - [Fourier Neural Operator](https://github.com/neuraloperator/neuraloperator) - Learning operators in Fourier space
 - [Poseidon](https://github.com/camlab-ethz/poseidon) - Efficient foundation models for PDEs with pretrained transformer-based neural operators and downstream task fine-tuning pipelines, HuggingFace integration for models and datasets (ETH Zurich CAMLab, arXiv 2024)
 - [GAOT (NeurIPS 2025)](https://github.com/camlab-ethz/GAOT) - Geometry Aware Operator Transformer serving as an efficient and accurate neural surrogate for PDEs on arbitrary domains, combining geometric priors with transformer architectures for scientific computing (ETH Zurich CAMLab, 92+ stars)
+- [TensorMesh (ETH Zurich CAMLab, arXiv 2026)](https://github.com/camlab-ethz/TensorMesh) - Fast, differentiable, JIT-free finite element library for PyTorch enabling GPU-native PDE solving with native autograd, tensorized assembly, and sparse linear algebra; part of the TensorGalerkin framework (218+ stars, Apache 2.0)
 - [PhiFlow](https://github.com/tum-pbs/PhiFlow) - Differentiable PDE solving framework for machine learning with built-in fluid simulation, supporting PyTorch/JAX/TensorFlow backends and enabling neural network training within physical simulations (TUM, MIT License)
 - [exponax](https://github.com/Ceyron/exponax) - Efficient differentiable n-dimensional PDE solvers built on JAX and Equinox, shipping 46+ built-in equations with Fourier spectral methods, exponential time differencing, and full auto-differentiation for physics-based deep learning workflows (MIT, 200+ stars, 2024)