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End-to-End Differentiable Reactive Molecular Dynamics Simulations Using JAX.

M. Kaymak, S. Schoenholz, E. Cubuk, K. O'Hearn, K. Jr., и H. Aktulga. ISC, том 13948 из Lecture Notes in Computer Science, стр. 202-219. Springer, (2023)

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Ekin Celik

Ekin Kozal

Halis Ruhi Ekingen

Seyhan Cubukcu

Turhan Cubukcu

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AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty.D. Hendrycks, N. Mu, E. Cubuk, B. Zoph, J. Gilmer, и B. Lakshminarayanan. CoRR, (2019)Learning Data Augmentation Strategies for Object Detection.B. Zoph, E. Cubuk, G. Ghiasi, T. Lin, J. Shlens, и Q. Le. ECCV (27), том 12372 из Lecture Notes in Computer Science, стр. 566-583. Springer, (2020)RandAugment: Practical data augmentation with no separate search.E. Cubuk, B. Zoph, J. Shlens, и Q. Le. CoRR, (2019)Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation.G. Ghiasi, Y. Cui, A. Srinivas, R. Qian, T. Lin, E. Cubuk, Q. Le, и B. Zoph. CoRR, (2020)AutoAugment: Learning Augmentation Strategies From Data.E. Cubuk, B. Zoph, D. Mané, V. Vasudevan, и Q. Le. CVPR, стр. 113-123. Computer Vision Foundation / IEEE, (2019)Affinity and Diversity: Quantifying Mechanisms of Data Augmentation.R. Lopes, S. Smullin, E. Cubuk, и E. Dyer. CoRR, (2020)Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation.L. Chen, R. Lopes, B. Cheng, M. Collins, E. Cubuk, B. Zoph, H. Adam, и J. Shlens. CoRR, (2020)Using learned optimizers to make models robust to input noise.L. Metz, N. Maheswaranathan, J. Shlens, J. Sohl-Dickstein, и E. Cubuk. CoRR, (2019)G-Augment: Searching for the Meta-Structure of Data Augmentation Policies for ASR.G. Wang, E. Cubuk, A. Rosenberg, S. Cheng, R. Weiss, B. Ramabhadran, P. Moreno, Q. Le, и D. Park. SLT, стр. 23-30. IEEE, (2022)SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition.D. Park, W. Chan, Y. Zhang, C. Chiu, B. Zoph, E. Cubuk, и Q. Le. INTERSPEECH, стр. 2613-2617. ISCA, (2019)

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