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Items where Author is "Csiszárik, Adrián"

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Number of items: 7.

Article

Csiszárik, Adrián and F. Kiss, Melinda and Kőrösi-Szabó, Péter and Muntag, Márton and Papp, Gergely and Varga, Dániel (2024) Mode combinability: Exploring convex combinations of permutation aligned models. NEURAL NETWORKS, 173. ISSN 0893-6080

Ambrus, Gergely and Csiszárik, Adrián and Matolcsi, Máté and Varga, Dániel and Zsámboki, Pál (2023) The density of planar sets avoiding unit distances. MATHEMATICAL PROGRAMMING. ISSN 0025-5610 (In Press)

Varga, Dániel and Csiszárik, Adrián and Zombori, Zsolt (2018) Gradient Regularization Improves Accuracy of Discriminative Models. Schedae Informaticae, 27. pp. 31-45. ISSN 0860-0295

Book Section

Zombori, Zsolt and Csiszárik, Adrián and Michalewski, Henryk and Kaliszyk, Cezary and Urban, Josef (2021) Towards Finding Longer Proofs. In: Automated Reasoning with Analytic Tableaux and Related Methods : 30th International Conference, TABLEAUX 2021, Birmingham, UK, September 6–9, 2021, Proceedings. Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence (12842). Springer Nature Switzerland AG. (Springer Nature), Cham, pp. 1-25. ISBN 978-3-030-86058-5 (softcover); 978-3-030-86059-2 (eBook)

Conference or Workshop Item

Csiszárik, Adrián and Kőrösi-Szabó, Péter and Matszangosz, Ákos K. and Papp, Gergely and Varga, Dániel (2021) Similarity and Matching of Neural Network Representations. In: Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), 2021.12.06-14., online.

Zombori, Zsolt and Csiszárik, Adrián and Michalewski, Henryk and Kaliszyk, Cezary and Urban, Josef (2020) Update on FLoP, a Reinforcement Learning based Theorem Prover. In: 5th Conference on Artificial Intelligence and Theorem Proving, 2020.09.13-2020.09.19, Aussois.

Csiszárik, Adrián and Benkő, Beatrix and Varga, Dániel (2019) Negative Sampling in Variational Autoencoders. In: 4th Workshop on Bayesian Deep Learning (NeurIPS 2019), 2019.12.13, Vancouver, Canada.

This list was generated on Fri Mar 29 14:40:15 2024 CET.