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Score-Based Generative Modeling through Stochastic Differential Equations

Y. Song, J. Sohl-Dickstein, D. Kingma, A. Kumar, S. Ermon, и B. Poole. (2020)cite arxiv:2011.13456Comment: ICLR 2021 (Oral).

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Jascha Sohl-Dickstein

Jascha Kehr

Jascha Melomedov

Michael Dickstein

Gisela Sohl

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Understanding and correcting pathologies in the training of learned optimizers.L. Metz, N. Maheswaranathan, J. Nixon, C. Freeman, и J. Sohl-Dickstein. ICML, том 97 из Proceedings of Machine Learning Research, стр. 4556-4565. PMLR, (2019)Unrolled Generative Adversarial Networks.L. Metz, B. Poole, D. Pfau, и J. Sohl-Dickstein. ICLR (Poster), OpenReview.net, (2017)The large learning rate phase of deep learning: the catapult mechanismA. Lewkowycz, Y. Bahri, E. Dyer, J. Sohl-Dickstein, и G. Gur-Ari. arXiv preprint arXiv:2003.02218, (2020)Towards NNGP-guided Neural Architecture Search.D. Park, J. Lee, D. Peng, Y. Cao, и J. Sohl-Dickstein. CoRR, (2020)Infinite attention: NNGP and NTK for deep attention networks.J. Hron, Y. Bahri, J. Sohl-Dickstein, и R. Novak. ICML, том 119 из Proceedings of Machine Learning Research, стр. 4376-4386. PMLR, (2020)Neural Tangents: Fast and Easy Infinite Neural Networks in Python.R. Novak, L. Xiao, J. Hron, J. Lee, A. Alemi, J. Sohl-Dickstein, и S. Schoenholz. ICLR, OpenReview.net, (2020)Deep Neural Networks as Gaussian Processes.J. Lee, Y. Bahri, R. Novak, S. Schoenholz, J. Pennington, и J. Sohl-Dickstein. ICLR (Poster), OpenReview.net, (2018)Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.A. Srivastava, A. Rastogi, A. Rao, A. Shoeb, A. Abid, A. Fisch, A. Brown, A. Santoro, A. Gupta, A. Garriga-Alonso и 440 other автор(ы). CoRR, (2022)Language Model CascadesD. Dohan, W. Xu, A. Lewkowycz, J. Austin, D. Bieber, R. Lopes, Y. Wu, H. Michalewski, R. Saurous, J. Sohl dickstein и 2 other автор(ы). (2022)cite arxiv:2207.10342Comment: Presented as spotlight at the Beyond Bases workshop at ICML 2022 (https://beyond-bayes.github.io).Neural Tangents: Fast and Easy Infinite Neural Networks in Python.R. Novak, L. Xiao, J. Hron, J. Lee, A. Alemi, J. Sohl-Dickstein, и S. Schoenholz. CoRR, (2019)

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