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Recent Vision-Language Pretrained (VLP) models have become the backbone for many downstream tasks, but they are utilized as frozen model without learning.
The Variational Formulation of the Fokker–Planck Equation
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Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories
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Automated flower classification over a large number of classes
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Imagenet: A large-scale hierarchical image database
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Sun database: Large-scale scene recognition from abbey to zoo
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UCF101: A dataset of 101 human actions classes from videos in the wild
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3d object representations for fine-grained categorization
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Fine-grained visual classification of aircraft
Maji, S.; Rahtu, E.; Kannala, J.; Blaschko, M.; and Vedaldi, A. 2013 · 2013
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Food-101–mining discriminative components with random forests
Bossard, L.; Guillaumin, M.; and Van Gool, L. 2014 · 2014
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Cimpoi, M.; Maji, S.; Kokkinos, I.; Mohamed, S.; and Vedaldi, A. 2014 · 2014
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Deep residual learning for image recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
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Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm
Liu, Q.; and Wang, D. 2016 · 2016
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A Unified Particle-Optimization Framework for Scalable Bayesian Sampling
Scaling up visual and vision-language representation learning with noisy text supervision
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Learning transferable visual models from natural language supervision
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Decomposed mutual information estimation for contrastive representation learning
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PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior
gil Lee, S.; Kim, H.; Shin, C.; Tan, X.; Liu, C.; Meng, Q.; Qin, T.; Chen, W.; Yoon, S.; and Liu, T.-Y. 2022 · 2022
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Prompt distribution learning
Lu, Y.; Liu, J.; Zhang, Y.; Liu, Y.; and Tian, X. 2022 · 2022
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Chen, C.; Zhang, R.; Wang, W.; Li, B.; and Chen, L. 2018 · 2018
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Umap: Uniform manifold approximation and projection for dimension reduction
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Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification
Helber, P.; Bischke, B.; Dengel, A.; and Borth, D. 2019 · 2019
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Do imagenet classifiers generalize to imagenet?
Recht, B.; Roelofs, R.; Schmidt, L.; and Shankar, V. 2019 · 2019
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Learning robust global representations by penalizing local predictive power
Wang, H.; Ge, S.; Lipton, Z.; and Xing, E. P. 2019 · 2019
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Data-dependent Gaussian Prior Objective for Language Generation
Li, Z.; Wang, R.; Chen, K.; Utiyama, M.; Sumita, E.; Zhang, Z.; and Zhao, H. 2020 · 2020
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The many faces of robustness: A critical analysis of out-of-distribution generalization
Hendrycks, D.; Basart, S.; Mu, N.; Kadavath, S.; Wang, F.; Dorundo, E.; Desai, R.; Zhu, T.; Parajuli, S.; Guo, M.; et al. 2021a
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Optimal Representations for Covariate Shift
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How Much Can CLIP Benefit Vision-and-Language Tasks?
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Robust fine-tuning of zero-shot models
Wortsman, M.; Ilharco, G.; Kim, J. W.; Li, M.; Kornblith, S.; Roelofs, R.; Lopes, R. G.; Hajishirzi, H.; Farhadi, A.; Namkoong, H.; et al. 2022 · 2022
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PLOT: Prompt Learning with Optimal Transport for Vision-Language Models
Chen, G.; Yao, W.; Song, X.; Li, X.; Rao, Y.; and Zhang, K. 2023 · 2023
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Bayesian Prompt Learning for Image-Language Model Generalization
Derakhshani, M. M.; Sanchez, E.; Bulat, A.; da Costa, V. G. T.; Snoek, C. G. M.; Tzimiropoulos, G.; and Martinez, B. 2023 · 2023
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