Transformation operators for spherical Schrödinger operators von Holzleitner, Markus

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Dispersion estimates for spherical Schrödinger equations: the effect of boundary conditions von Holzleitner, Markus, Kostenko, Aleksey, Teschl, Gerald

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On regularized polynomial functional regression von Holzleitner, Markus, Pereverzyev, Sergei V.

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Convergence Proof for Actor-Critic Methods Applied to PPO and RUDDER von Holzleitner, Markus, Gruber, Lukas, Arjona-Medina, José, Brandstetter, Johannes, Hochreiter, Sepp

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Properties of the scattering matrix and dispersion estimates for Jacobi operators von Egorova, Iryna, Holzleitner, Markus, Teschl, Gerald

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On regularized polynomial functional regression von Holzleitner, Markus, Pereverzyev, Sergei

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Zero energy scattering for one-dimensional Schrödinger operators and applications to dispersive estimates von Egorova, Iryna, Holzleitner, Markus, Teschl, Gerald

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Transformation operators for spherical Schr\"odinger operators von Holzleitner, Markus

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Domain Generalization by Functional Regression von Holzleitner, Markus, Pereverzyev, Sergei V, Zellinger, Werner

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Overcoming Saturation in Density Ratio Estimation by Iterated Regularization von Gruber, Lukas, Holzleitner, Markus, Lehner, Johannes, Hochreiter, Sepp, Zellinger, Werner

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Transformation operators for spherical Schrödinger operators von Holzleitner, Markus

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Multiparameter regularization and aggregation in the context of polynomial functional regression von Gizewski, Elke R, Holzleitner, Markus, Mayer-Suess, Lukas, PereverzyevJr, Sergiy, Pereverzyev, Sergei V

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Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators von Alkin, Benedikt, Fürst, Andreas, Schmid, Simon, Gruber, Lukas, Holzleitner, Markus, Brandstetter, Johannes

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SymbolicAI: A framework for logic-based approaches combining generative models and solvers von Dinu, Marius-Constantin, Leoveanu-Condrei, Claudiu, Holzleitner, Markus, Zellinger, Werner, Hochreiter, Sepp

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Overcoming Saturation in Density Ratio Estimation by Iterated Regularization von Gruber, Lukas, Holzleitner, Markus, Lehner, Johannes, Hochreiter, Sepp, Zellinger, Werner

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Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation von Dinu, Marius-Constantin, Holzleitner, Markus, Beck, Maximilian, Nguyen, Hoan Duc, Huber, Andrea, Eghbal-zadeh, Hamid, Moser, Bernhard A, Pereverzyev, Sergei, Hochreiter, Sepp, Zellinger, Werner

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History Compression via Language Models in Reinforcement Learning von Paischer, Fabian, Adler, Thomas, Patil, Vihang, Bitto-Nemling, Angela, Holzleitner, Markus, Lehner, Sebastian, Eghbal-zadeh, Hamid, Hochreiter, Sepp

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Convergence Proof for Actor-Critic Methods Applied to PPO and RUDDER von Holzleitner, Markus, Gruber, Lukas, Arjona-Medina, José, Brandstetter, Johannes, Hochreiter, Sepp

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Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators von Alkin, Benedikt, Fürst, Andreas, Schmid, Simon, Gruber, Lukas, Holzleitner, Markus, Brandstetter, Johannes

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Few-Shot Learning by Dimensionality Reduction in Gradient Space von Gauch, Martin, Beck, Maximilian, Adler, Thomas, Kotsur, Dmytro, Fiel, Stefan, Eghbal-zadeh, Hamid, Brandstetter, Johannes, Kofler, Johannes, Holzleitner, Markus, Zellinger, Werner, Klotz, Daniel, Hochreiter, Sepp, Lehner, Sebastian

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