Sayna Ebrahimi

According to our database1, Sayna Ebrahimi authored at least 29 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
TextGenSHAP: Scalable Post-hoc Explanations in Text Generation with Long Documents.
CoRR, 2023

PAITS: Pretraining and Augmentation for Irregularly-Sampled Time Series.
CoRR, 2023

LANISTR: Multimodal Learning from Structured and Unstructured Data.
CoRR, 2023

ASPEST: Bridging the Gap Between Active Learning and Selective Prediction.
CoRR, 2023

Beyond Invariance: Test-Time Label-Shift Adaptation for Addressing "Spurious" Correlations.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022
Beyond Invariance: Test-Time Label-Shift Adaptation for Distributions with "Spurious" Correlations.
CoRR, 2022

Test-Time Adaptation for Visual Document Understanding.
CoRR, 2022

Self-Supervised Pretraining Improves Self-Supervised Pretraining.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Differentiable Gradient Sampling for Learning Implicit 3D Scene Reconstructions from a Single Image.
Proceedings of the Tenth International Conference on Learning Representations, 2022

DualPrompt: Complementary Prompting for Rehearsal-Free Continual Learning.
Proceedings of the Computer Vision - ECCV 2022, 2022

Contrastive Test-Time Adaptation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
On-target Adaptation.
CoRR, 2021

Region-level Active Learning for Cluttered Scenes.
CoRR, 2021

Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting.
Proceedings of the 9th International Conference on Learning Representations, 2021

Predicting with Confidence on Unseen Distributions.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Mechanical Behavior of Materials at Multiscale Peridynamic Theory and Learning-based Approaches.
PhD thesis, 2020

Compositional GAN: Learning Image-Conditional Binary Composition.
Int. J. Comput. Vis., 2020

Minimax Active Learning.
CoRR, 2020

Uncertainty-guided Continual Learning with Bayesian Neural Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020

Adversarial Continual Learning.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
Compositional GAN (Extended Abstract): Learning Image-Conditional Binary Composition.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

Variational Adversarial Active Learning.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Generalized Zero-Shot Learning via Aligned Variational Autoencoders.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Uncertainty-Guided Continual Learning in Bayesian Neural Networks - Extended Abstract.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

WiCV 2019: The Sixth Women In Computer Vision Workshop.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

2018
Compositional GAN: Learning Conditional Image Composition.
CoRR, 2018

2017
Gradient-free Policy Architecture Search and Adaptation.
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017


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