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#GeometricDeepLearning

Latest posts tagged with #GeometricDeepLearning on Bluesky

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Posts tagged #GeometricDeepLearning

💻 GitHub: github.com/geometric-ke...
📄 JMLR Paper: www.jmlr.org/papers/v26/2...

#MachineLearning #GeometricDeepLearning #GaussianProcesses #Kernels #Graphs #Manifolds #JMLR #OpenSource

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How can voxels, meshes, and point clouds shape smarter AI in medicine?
Find out at the next #SanoSeminar by Marek Wodziński (Sano & AGH).
💻 Free online: sano.science/seminars/abs...
#AI #MedicalImaging #GeometricDeepLearning

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Encoding geometry in neural network architectures has wide applications, from robots' configuration spaces to safety. We present natural ways to enforce constraints by design.

Link to preprint: www.researchgate.net/publication/...

#geometricdeeplearning

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Symplectic Reservoir Representation of Legendre Dynamics Modern learning systems act on internal representations of data, yet how these representations encode underlying physical or statistical structure is often left implicit. In physics, conservation laws...

Beyond metric preservation: build symplectic structural invariance into representation.

arxiv.org/abs/2512.19409

#ReservoirComputing #RepresentationLearning #InformationGeometry #SymplecticGeometry #HamiltonianDynamics #GeometricDeepLearning #DynamicalSystems #PhysicsInformedML

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#GenerativeAI #GraphNeuralNetworks #ComputerVision #Hypergraphs #GeometricDeepLearning

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🤓 We match or achieve SotA results among TDL models with orders of magnitude less complexity!

🫂 Amazing joint work with @GDasoulas, @mauriciogtec, @ekarais43, @audiracmichelle, @francescadomin8

#TopologicalDeepLearning #GeometricDeepLearning #EquivariantNeuralNetworks

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"gRNAde: Geometric Deep Learning for 3D RNA inverse design" by @chaitjo.bsky.social , @arian-jamasb.bsky.social, Ramon Viñas, Charles Harris, Simon Mathis, Alex Morehead, Rishabh Anand, and Pietro Liò

Paper: www.biorxiv.org/content/10.1...

Code: github.com/chaitjo/geom...

#geometricdeeplearning

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"Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges" by @mmbronstein.bsky.social, Joan Bruna, Taco Cohen, @petar-v.bsky.social

#geometricdeeplearning

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📏We adapt existing graph neural networks and transformers to take neural graphs as input, and incorporate inductive biases from neural graphs.
In the context of #geometricdeeplearning, neural graphs constitute a new benchmark for graph neural networks.
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A geometric deep learning approach to predict binding conformations of bioactive molecules Nature Machine Intelligence - Predicting binding of ligands to molecular targets is a key task in the development of new drugs. To improve the speed and accuracy of this prediction,...

Very nice presentation by @omendezlucio about their recently published piece using #geometricdeeplearning to predict protein-ligand binding interactions #drugdiscovery #artificialintelligence

nature.com/articles/s4225…

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