Primordial power spectra from k -inflation with curvature von Shumaylov, Zakhar, Handley, Will

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AI models collapse when trained on recursively generated data von Shumailov, Ilia, Shumaylov, Zakhar, Zhao, Yiren, Papernot, Nicolas, Anderson, Ross, Gal, Yarin

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Primordial power spectra from $k$-inflation with curvature von Shumaylov, Zakhar, Handley, Will

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Score-based pullback Riemannian geometry von Diepeveen, Willem, Batzolis, Georgios, Shumaylov, Zakhar, Schönlieb, Carola-Bibiane

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Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation von Shumaylov, Zakhar, Budd, Jeremy, Mukherjee, Subhadip, Schönlieb, Carola-Bibiane

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Provably Convergent Data-Driven Convex-Nonconvex Regularization von Shumaylov, Zakhar, Budd, Jeremy, Mukherjee, Subhadip, Schönlieb, Carola-Bibiane

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Primordial power spectra from \(k\)-inflation with curvature von Shumaylov, Zakhar, Handley, Will

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Symplectic Neural Flows for Modeling and Discovery von Canizares, Priscilla, Murari, Davide, Schönlieb, Carola-Bibiane, Sherry, Ferdia, Shumaylov, Zakhar

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Hamiltonian Matching for Symplectic Neural Integrators von Canizares, Priscilla, Murari, Davide, Schönlieb, Carola-Bibiane, Sherry, Ferdia, Shumaylov, Zakhar

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Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups von Shumaylov, Zakhar, Zaika, Peter, Rowbottom, James, Sherry, Ferdia, Weber, Melanie, Schönlieb, Carola-Bibiane

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AI models collapse when trained on recursively generated data von Shumailov, Ilia, Shumaylov, Zakhar, Zhao, Yiren, Papernot, Nicolas, Anderson, Ross, Gal, Yarin

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Benchmarking learned algorithms for computed tomography image reconstruction tasks von Kiss, Maximilian B, Biguri, Ander, Shumaylov, Zakhar, Sherry, Ferdia, Batenburg, K. Joost, Schönlieb, Carola-Bibiane, Lucka, Felix

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Quantum initial conditions for curved inflating universes von Letey, Mary I, Shumaylov, Zakhar, Agocs, Fruzsina J, Handley, Will J, Hobson, Michael P, Lasenby, Anthony N

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The Curse of Recursion: Training on Generated Data Makes Models Forget von Shumailov, Ilia, Shumaylov, Zakhar, Zhao, Yiren, Gal, Yarin, Papernot, Nicolas, Anderson, Ross

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Score-based pullback Riemannian geometry von Diepeveen, Willem, Batzolis, Georgios, Shumaylov, Zakhar, Schönlieb, Carola-Bibiane

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Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation von Shumaylov, Zakhar, Budd, Jeremy, Mukherjee, Subhadip, Schönlieb, Carola-Bibiane

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Provably Convergent Data-Driven Convex-Nonconvex Regularization von Shumaylov, Zakhar, Budd, Jeremy, Mukherjee, Subhadip, Schönlieb, Carola-Bibiane

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Manipulating SGD with Data Ordering Attacks von Shumailov, Ilia, Shumaylov, Zakhar, Kazhdan, Dmitry, Zhao, Yiren, Papernot, Nicolas, Erdogdu, Murat A, Anderson, Ross

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Symplectic Neural Flows for Modeling and Discovery von Canizares, Priscilla, Murari, Davide, Schönlieb, Carola-Bibiane, Ferdia Sherry, Shumaylov, Zakhar

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Hamiltonian Matching for Symplectic Neural Integrators von Canizares, Priscilla, Murari, Davide, Schönlieb, Carola-Bibiane, Ferdia Sherry, Shumaylov, Zakhar

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