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Learning Invariances in Neural Networks from Training Data.

, , , и . NeurIPS, (2020)

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Leo Finzi

Moritz Mosko Finzi

Stefanie Marczoch

Langzeitverlauf von 200 Patienten mit kraniofazialen und zervikalen Dystonien bis zu 12 Jahre nach der ersten Botulinumtoxin-Behandlung. TU München, (2009)

Hans-Peter Marchal

Erna Marcus

 

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Large Language Models Are Zero-Shot Time Series Forecasters., , , и . CoRR, (2023)Residual Pathway Priors for Soft Equivariance Constraints., , и . NeurIPS, стр. 30037-30049. (2021)PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization., , , , , и . NeurIPS, (2022)Learning Invariances in Neural Networks from Training Data., , , и . NeurIPS, (2020)Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints., , и . NeurIPS, (2020)Semi-Supervised Learning with Normalizing Flows, , , и . (2019)cite arxiv:1912.13025.There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average., , , и . ICLR (Poster), OpenReview.net, (2019)Semi-Supervised Learning with Normalizing Flows., , , и . ICML, том 119 из Proceedings of Machine Learning Research, стр. 4615-4630. PMLR, (2020)Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data., , , и . ICML, том 119 из Proceedings of Machine Learning Research, стр. 3165-3176. PMLR, (2020)SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes., , , и . ICML, том 139 из Proceedings of Machine Learning Research, стр. 5279-5289. PMLR, (2021)