FOUNDATIONS OF STRUCTURAL CAUSAL MODELS WITH CYCLES AND LATENT VARIABLES von Bongers, Stephan, Forre, Patrick, Peters, Jonas, Mooij, Joris M.

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Bayesian optimization of comprehensive two-dimensional liquid chromatography separations von Boelrijk, Jim, Pirok, Bob, Ensing, Bernd, Forré, Patrick

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Chemometric Strategies for Fully Automated Interpretive Method Development in Liquid Chromatography von Bos, Tijmen S., Boelrijk, Jim, Molenaar, Stef R. A., van ’t Veer, Brian, Niezen, Leon E., van Herwerden, Denice, Samanipour, Saer, Stoll, Dwight R., Forré, Patrick, Ensing, Bernd, Somsen, Govert W., Pirok, Bob W. J.

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Closed-loop automatic gradient design for liquid chromatography using Bayesian optimization von Boelrijk, Jim, Ensing, Bernd, Forré, Patrick, Pirok, Bob W.J.

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Predicting RP-LC retention indices of structurally unknown chemicals from mass spectrometry data von Boelrijk, Jim, van Herwerden, Denice, Ensing, Bernd, Forré, Patrick, Samanipour, Saer

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Lightweight super-resolution multimode fiber imaging with regularized linear regression von Lipp, Maximilian, Li, Wei, Abrashitova, Ksenia, Forré, Patrick, Amitonova, Lyubov V

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The kernel of the reciprocity map of varieties over local fields von Forré, Patrick

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Strongly free sequences and pro-p-groups of cohomological dimension 2 von Forré, Patrick

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Pruning by leveraging training dynamics von Apostol, Andrei C., Stol, Maarten C., Forré, Patrick

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The Kernel of the Reciprocity Map of Simple Normal Crossing Varieties over Finite Fields von Forre, Patrick

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SB1-1 Markov Properties for Non-linear Structural Causal Models with Cycles and Latent Confounders von Forré, Patrick

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Learning to predict spatiotemporal movement dynamics from weather radar networks von Lippert, Fiona, Kranstauber, Bart, Forré, Patrick D., Loon, E. Emiel

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Enhancing LC×LC separations through multi-task Bayesian optimization von Boelrijk, Jim, Molenaar, Stef R.A., Bos, Tijmen S., Dahlseid, Tina A., Ensing, Bernd, Stoll, Dwight R., Forré, Patrick, Pirok, Bob W.J.

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Quasi-Measurable Spaces von Forré, Patrick

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Transitional Conditional Independence von Forré, Patrick

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Lie Group Decompositions for Equivariant Neural Networks von Mironenco, Mircea, Forré, Patrick

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Multi-View Independent Component Analysis with Shared and Individual Sources von Pandeva, Teodora, Forré, Patrick

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Nonparametric Bayesian networks are typically faithful in the total variation metric von Boeken, Philip, Forré, Patrick, Mooij, Joris M

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Self-Supervised Inference in State-Space Models von Ruhe, David, Forré, Patrick

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Multivector Neurons: Better and Faster O(n)-Equivariant Clifford Graph Neural Networks von Liu, Cong, Ruhe, David, Forré, Patrick

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