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2020 – today
- 2023
[j1]Belinda Tzen, Anant Raj
, Maxim Raginsky, Francis R. Bach:
Variational Principles for Mirror Descent and Mirror Langevin Dynamics. IEEE Control. Syst. Lett. 7: 1542-1547 (2023)- [i5]Belinda Tzen, Anant Raj, Maxim Raginsky, Francis R. Bach:
Variational Principles for Mirror Descent and Mirror Langevin Dynamics. CoRR abs/2303.09532 (2023) - 2020
- [i4]Belinda Tzen, Maxim Raginsky:
A mean-field theory of lazy training in two-layer neural nets: entropic regularization and controlled McKean-Vlasov dynamics. CoRR abs/2002.01987 (2020)
2010 – 2019
- 2019
- [c2]Belinda Tzen, Maxim Raginsky:
Theoretical guarantees for sampling and inference in generative models with latent diffusions. COLT 2019: 3084-3114 - [i3]Belinda Tzen, Maxim Raginsky:
Theoretical guarantees for sampling and inference in generative models with latent diffusions. CoRR abs/1903.01608 (2019) - [i2]Belinda Tzen, Maxim Raginsky:
Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit. CoRR abs/1905.09883 (2019) - 2018
- [c1]Belinda Tzen, Tengyuan Liang, Maxim Raginsky:
Local Optimality and Generalization Guarantees for the Langevin Algorithm via Empirical Metastability. COLT 2018: 857-875 - [i1]Belinda Tzen, Tengyuan Liang, Maxim Raginsky:
Local Optimality and Generalization Guarantees for the Langevin Algorithm via Empirical Metastability. CoRR abs/1802.06439 (2018)
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