--- id: "/science-medicine/expert/page/5/" title: "Science & medicine for expert learners · page 5" url: "https://skillissue.dev/science-medicine/expert/page/5/" --- # Science & medicine for expert learners [Beginner](/science-medicine/beginner/index.md) [Intermediate](/science-medicine/intermediate/index.md) [Advanced](/science-medicine/advanced/index.md) [Expert](/science-medicine/expert/index.md) 160 resources · page 5 of 5 - ### [SpyTorch](/frontier/research-feeds/spytorch-spiking-nns-tutorial/index.md) by [Friedemann Zenke](https://fzenke.net) SpyTorch GitHub repo: tutorial on surrogate gradient learning in spiking neural networks. entity repo West en - ### [State Council Opinions on Deepening the "AI+" Action (国务院关于深入实施"人工智能+"行动的意见)](/frontier/research-feeds/state-council-opinions-on-deepening-the-ai-action/index.md) by [State Council of the People's Republic of China](https://www.gov.cn/) China State Council opinions (August 2025) on deepening the AI+ action across the economy. entity standard-policy China zh - ### [TerraTorch](/frontier/research-feeds/terratorch/index.md) by [TorchGeo](https://torchgeo.org/) TerraTorch GitHub repo: toolkit for fine-tuning geospatial foundation models. entity repo Global en - ### [The Well dataset](/frontier/research-feeds/the-well-dataset/index.md) by [Polymathic AI](https://polymathic-ai.org) Polymathic AI The Well GitHub repo: 15TB collection of physics simulation datasets for machine learning. entity repo West en - ### [TorchANI](/frontier/research-feeds/torchani/index.md) by [AIQM](https://github.com/aiqm) TorchANI GitHub repo: library for training and using ANI neural network potentials for molecules. entity repo US; international en - ### [TxGNN](/frontier/research-feeds/txgnn/index.md) by [Artificial Intelligence for Medicine and Science @ Harvard Zitnik Lab](https://zitniklab.hms.harvard.edu) Harvard TxGNN GitHub repo: graph model for zero-shot prediction of drug repurposing. entity repo US en - ### [UNI (Mahmood Lab) pathology foundation model](/frontier/research-feeds/uni-mahmood-lab-pathology-foundation-model/index.md) by [Mahmood Lab @ Harvard/MGB](https://www.mahmoodlab.org) Mahmood Lab UNI GitHub repo: pathology foundation model (Nature Medicine) with weights and embeddings. entity model US en - ### [Uni-Mol](/frontier/research-feeds/uni-mol/index.md) by [DeepModeling](https://deepmodeling.com) Uni-Mol GitHub repo (DP Technology): 3D molecular pretraining models for property prediction and docking. entity model China en - ### [Wildlife Insights](/frontier/research-feeds/wildlife-insights/index.md) by [Wildlife Insights](https://wildlifeinsights.org/) Wildlife Insights: platform using machine learning to identify species in camera-trap images for conservation. entity company Global en - ### [Zooniverse](/frontier/research-feeds/zooniverse/index.md) by [Zooniverse](https://zooniverse.org/) Zooniverse: citizen-science platform whose volunteer labels support research projects and train ML models. entity company UK/Global mul - ### [AIFS paper (ECMWF)](/frontier/research-feeds/aifs-paper-ecmwf/index.md) by [Simon Lang et al. (ECMWF)](https://www.ecmwf.int/) arXiv paper (2024) describing AIFS, ECMWF's data-driven weather forecasting system. Advanced–Expert learning_resource paper West en - ### [Aurora](/frontier/research-feeds/aurora/index.md) by [Cristian Bodnar et al. (Microsoft)](https://www.microsoft.com/) arXiv HTML version of the Aurora paper (2024) on a foundation model of the atmosphere. Advanced–Expert learning_resource paper Global (Microsoft Research; Ca en - ### [ClimaX](/frontier/research-feeds/climax/index.md) by [Tung Nguyen et al. (UCLA and Microsoft Research)](https://www.microsoft.com/en-us/research/) ICML 2023 paper ClimaX: a foundation model for weather and climate. Advanced–Expert learning_resource paper Global (Microsoft Research; UC en - ### [DeepONet (Lu et al.)](/frontier/research-feeds/deeponet-lu-et-al/index.md) by [Lu Lu et al. (Brown University)](https://www.brown.edu/) arXiv paper (2019) introducing DeepONet for learning nonlinear operators of differential equations. Advanced–Expert learning_resource paper West en - ### [Fourier Neural Operator (Li et al.)](/frontier/research-feeds/fourier-neural-operator-li-et-al/index.md) by [Zongyi Li et al. (Caltech)](https://www.caltech.edu/) arXiv paper (2020) introducing the Fourier Neural Operator for learning parametric PDE solutions. Advanced–Expert learning_resource paper West en - ### [GenCast paper](/frontier/research-feeds/gencast-paper/index.md) by [Ilan Price et al. (Google DeepMind)](https://deepmind.google/) arXiv paper (2023) introducing GenCast, a diffusion-based ensemble model for medium-range weather forecasting. Advanced–Expert learning_resource paper West en - ### [GraphCast paper](/frontier/research-feeds/graphcast-paper/index.md) by [Remi Lam et al. (Google DeepMind)](https://deepmind.google/) arXiv paper (2022) introducing GraphCast, a graph neural network for medium-range global weather forecasting. Advanced–Expert learning_resource paper West en - ### [KAN: Kolmogorov-Arnold Networks](/frontier/research-feeds/kan-kolmogorov-arnold-networks/index.md) by [Ziming Liu et al. (MIT)](https://www.mit.edu/) arXiv paper (2024) introducing Kolmogorov-Arnold Networks (KAN) with learnable activation functions on edges. Advanced–Expert learning_resource paper West en - ### [Learning to Simulate Complex Physics with Graph Networks (GNS)](/frontier/research-feeds/learning-to-simulate-complex-physics-with-graph-networks-gns/index.md) by [Alvaro Sanchez-Gonzalez et al. (Google)](https://ai.google/) arXiv paper (2020) introducing Graph Network-based Simulators (GNS) for learning complex particle physics. Advanced–Expert learning_resource paper West en - ### [MeshGraphNets](/frontier/research-feeds/meshgraphnets/index.md) by [Tobias Pfaff et al. (Google)](https://ai.google/) arXiv paper (2020) introducing MeshGraphNets for learning mesh-based physical simulation. Advanced–Expert learning_resource paper West en - ### [Neural Operator: Learning maps between function spaces](/frontier/research-feeds/neural-operator-learning-maps-between-function-spaces/index.md) by [Nikola Kovachki et al. (Caltech)](https://www.caltech.edu/) arXiv paper (2021) "Neural Operator: Learning Maps Between Function Spaces", the general framework covering Fourier and graph neural operators for PDEs. Advanced–Expert learning_resource paper West en - ### [PaiNN](/frontier/research-feeds/painn/index.md) by [Kristof T. Schütt et al. (Technische Universität Berlin)](https://www.tu.berlin) arXiv HTML version of the PaiNN paper (2021) on equivariant message passing for molecular property prediction. Advanced–Expert learning_resource paper EU-DE en - ### [Physics-informed deep learning (Raissi et al.)](/frontier/research-feeds/physics-informed-deep-learning-raissi-et-al/index.md) by [Maziar Raissi et al. (Brown University)](https://www.brown.edu) arXiv paper (2017) introducing physics-informed neural networks (PINNs) for data-driven solutions of nonlinear PDEs. Advanced–Expert learning_resource paper West en - ### [SchNet: A continuous-filter convolutional neural network for modeling quantum interactions](/frontier/research-feeds/schnet/index.md) by [Kristof T. Schütt et al. (Technische Universität Berlin)](https://www.tu.berlin) arXiv paper (2017) introducing SchNet, a continuous-filter convolutional network for modelling quantum interactions in molecules. Advanced–Expert learning_resource paper West en - ### [SchNet: a deep learning architecture for molecules and materials](/frontier/research-feeds/schnet-2/index.md) by [Kristof T. Schütt et al. (Technische Universität Berlin)](https://www.tu.berlin) arXiv paper (2017) "SchNet - a deep learning architecture for molecules and materials", using continuous-filter convolutions to predict molecular energies and forces. Advanced–Expert learning_resource paper Global (TU Berlin/Max Planck; en - ### [Anemoi](/frontier/research-feeds/anemoi/index.md) by [ECMWF (Anemoi)](https://www.ecmwf.int/) Anemoi documentation: ECMWF-led framework for building data-driven weather forecasting models, from data to inference. Expert learning_resource docs Europe/intergovernmental en - ### [FAIR-Chem](/frontier/research-feeds/fair-chem/index.md) by [Meta Research](https://opensource.fb.com) FAIR Chemistry documentation: Meta's open datasets, models and workflows for atomistic chemistry and materials. Expert learning_resource docs US/global en - ### [Still Waters, Rapid Currents: Early Labor Market Transformation under Generative AI (NBER w33777)](/frontier/research-feeds/humlum-vestergaard-large-language-models-small-labor-market-effects-nber-w33777/index.md) by [National Bureau of Economic Research (NBER)](https://www.nber.org/) NBER working paper w33777 by Humlum and Vestergaard on early labour-market effects of AI chatbots, using Danish data. Expert learning_resource paper Denmark en - ### [NASA Autonomy Verification & Validation Roadmap and Vision 2045](/frontier/research-feeds/nasa-autonomy-verification-validation-roadmap-and-vision-2045/index.md) by [NASA](https://www.nasa.gov/) NASA technical report: Autonomy Verification and Validation Roadmap and Vision 2045 for learning-enabled aircraft systems. Expert learning_resource paper United States en - ### [NeuralOperator](/frontier/research-feeds/neuraloperator/index.md) by [NeuralOperator](https://neuraloperator.github.io/dev/index.html) NeuralOperator documentation: PyTorch library implementing Fourier and other neural operators for learning PDE solutions. Expert learning_resource docs US/global en - ### [NVIDIA PhysicsNeMo Framework documentation](/frontier/research-feeds/physicsnemo/index.md) by [NVIDIA](https://www.nvidia.com/) NVIDIA PhysicsNeMo documentation: framework for physics-informed ML and neural operators for simulation. Expert learning_resource docs US/global en - ### [SciML / DiffEqFlux documentation](/frontier/research-feeds/sciml-diffeqflux-documentation/index.md) by [SciML Open Source Scientific Machine Learning](https://sciml.ai/) DiffEqFlux.jl documentation: Julia library combining differential equation solvers with neural networks for scientific ML. 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