Citation notice #5062 · 2026-07-11 03:19:08.722131+00:00

Multivariate Distributional Reinforcement Learning Using Sliced Divergences

cites SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python, which carries a correction notice dated 2020-03-04. One-hop deterministic notice: the citation edge exists in the Pith bibliography graph; no model judged whether the citation was load-bearing.

This is not a judgment on the citing paper.

Citing paper Event page Original DOI Notice DOI File a formal challenge All reference changes

01Evidence

Raw extraction · bibliography line · bibliography index 3

Springer, 2008. Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., Carey, C. J., Polat, ˙I., Feng, Y ., Moore, E. W., VanderPlas, J., Laxalde, D., Perktold, J., Cimrman, R., Henriksen, I., Quintero, E. A., Harris, C. R., Archibald, A. M., Ribeiro, A. H., Pedregosa, F., van Mulbregt, P., and SciPy 1.0 Contributors. SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python.Nature Methods, 17:261–272, 2020. doi: 10.1038/s41592-019-0686-2. Wiltzer, H., Farebrother, J., Gretton, A., and Rowland, M. Foundations of multivariate distributional reinforcement learning.Advances in Neural Information Processing Systems, 37:101297–101336, 2024a. Wiltzer, H., Farebrother, J., Gretton, A., and Rowland, M. Foundations of multivariate distributional reinforcement learning, 2024b. URL https://arxiv.org/abs/ 2409.00328. Zhang, P., Chen, X., Zhao, L., Xiong, W., Qin, T., and Liu, T.-Y . Distributional reinforcement learning for multi- dimensional reward functions.Advances in Neura

02Event

Type

Correction

Source

Crossref

Original DOI

10.1038/s41592-019-0686-2

Notice DOI

10.1038/s41592-020-0772-5

Date

2020-03-04

Title

Author Correction: SciPy 1.0: fundamental algorithms for scientific computing in Python

Reasons

['Correction']

Work

SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python (2020) Nature Methods

Schema constants (for re-runners): correction · crossref

03Dispute this notice

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