Author of the publication

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and Restoration.

R. Liu, S. Khose, J. Xiao, L. Sathidevi, K. Ramnath, Z. Kira, and E. Dyer. WACV, page 2657-2667. IEEE, (2024)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Matthias Dyer

Michael Dyer

Éva L rinczi

Eva D L Böndel

Paul Dyer Merica

Other publications of authors with the same name

Bayesian optimization for modular black-box systems with switching costs.C. Lin, J. Miano, and E. Dyer. UAI, volume 161 of Proceedings of Machine Learning Research, page 1024-1034. AUAI Press, (2021)MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction.J. Quesada, L. Sathidevi, R. Liu, N. Ahad, J. Jackson, M. Azabou, J. Xiao, C. Liding, M. Jin, C. Urzay and 3 other author(s). CoRR, (2023)Bayesian optimization for modular black-box systems with switching costsC. Lin, J. Miano, and E. Dyer. (2020)cite arxiv:2006.02624.Making transport more robust and interpretable by moving data through a small number of anchor points.C. Lin, M. Azabou, and E. Dyer. ICML, volume 139 of Proceedings of Machine Learning Research, page 6631-6641. PMLR, (2021)Detecting change points in neural population activity with contrastive metric learning.C. Urzay, N. Ahad, M. Azabou, A. Schneider, G. Atamkuri, K. Hengen, and E. Dyer. NER, page 1-4. IEEE, (2023)Hierarchical Optimal Transport for Multimodal Distribution Alignment.J. Lee, M. Dabagia, E. Dyer, and C. Rozell. NeurIPS, page 13453-13463. (2019)Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity.F. Pei, J. Ye, D. Zoltowski, A. Wu, R. Chowdhury, H. Sohn, J. O'Doherty, K. Shenoy, M. Kaufman, M. Churchland and 6 other author(s). NeurIPS Datasets and Benchmarks, (2021)Hybrid modeling of non-stationary process variations.E. Dyer, M. Majzoobi, and F. Koushanfar. DAC, page 194-199. ACM, (2011)From sample to knowledge: Towards an integrated approach for neuroscience discovery.W. Roncal, E. Dyer, D. Gürsoy, K. Körding, and N. Kasthuri. CoRR, (2016)Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity.R. Liu, M. Azabou, M. Dabagia, C. Lin, M. Azar, K. Hengen, M. Valko, and E. Dyer. NeurIPS, page 10587-10599. (2021)

BibSonomy

Disambiguation of "Dyer, Eva L."

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and Restoration.

Please choose a person to relate this publication to

Matthias Dyer

Michael Dyer

Éva L rinczi

Eva D L Böndel

Paul Dyer Merica

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Dyer, Eva L."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and Restoration.

Please choose a person to relate this publication to

Matthias Dyer

Michael Dyer

Éva L rinczi

Eva D L Böndel

Paul Dyer Merica

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and Restoration.