Revisiting Bayesian Model Averaging in the Era of Foundation Models | Paper Citation Record

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This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Learning Transferable Visual Models From Natural Language Supervision

Reference 1

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This paper cites Imagenet: A large-scale hierarchical image database.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Imagenet: A large-scale hierarchical image database

Reference 2

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This paper cites Coca: Contrastive captioners are image-text foundation models.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Coca: Contrastive captioners are image-text foundation models

Reference 3

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This paper cites Eva-02: A visual representation for neon genesis.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Eva-02: A visual representation for neon genesis

Reference 4

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This paper cites Low-rank few-shot adaptation of vision-language models.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Low-rank few-shot adaptation of vision-language models

Reference 5

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This paper cites Robust fine-tuning of zero-shot models.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Robust fine-tuning of zero-shot models

Reference 6

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This paper cites The evolution of out-of-distribution robustness throughout fine-tuning.

Revisiting Bayesian Model Averaging in the Era of Foundation Models The evolution of out-of-distribution robustness throughout fine-tuning

Reference 7

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This paper cites Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time

Reference 8

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This paper cites Openclip, July 2021.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Openclip, July 2021

Reference 9

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Revisiting Bayesian Model Averaging in the Era of Foundation Models Unresolved cited work

Reference 10

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Revisiting Bayesian Model Averaging in the Era of Foundation Models Unresolved cited work

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This paper cites Pauler, Jonathan C.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Pauler, Jonathan C

Reference 12

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This paper cites Active learning of neural response functions with gaussian processes.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Active learning of neural response functions with gaussian processes

Reference 13

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This paper cites Heavy-tailed class imbalance and why adam outperforms gradient descent on language models.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Heavy-tailed class imbalance and why adam outperforms gradient descent on language models

Reference 14

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This paper cites What uncertainties do we need in bayesian deep learning for computer vision? In I.

Revisiting Bayesian Model Averaging in the Era of Foundation Models What uncertainties do we need in bayesian deep learning for computer vision? In I

Reference 15

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This paper cites Zico Kolter.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Zico Kolter

Reference 16

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This paper cites Linear Mode Connectivity and the Lottery Ticket Hypothesis.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Linear Mode Connectivity and the Lottery Ticket Hypothesis

Reference 17

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This paper cites What is being transferred in transfer learning?.

Revisiting Bayesian Model Averaging in the Era of Foundation Models What is being transferred in transfer learning?

Reference 18

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This paper cites Neural networks with late-phase weights.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Neural networks with late-phase weights

Reference 19

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This paper cites Merging Models with Fisher-Weighted Averaging.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Merging Models with Fisher-Weighted Averaging

Reference 20

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This paper cites Ensemble methods in machine learning.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Ensemble methods in machine learning

Reference 21

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This paper cites An empirical comparison of voting classification algorithms: Bagging, boosting, and variants.

Revisiting Bayesian Model Averaging in the Era of Foundation Models An empirical comparison of voting classification algorithms: Bagging, boosting, and variants

Reference 22

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Revisiting Bayesian Model Averaging in the Era of Foundation Models Bagging predictors

Reference 23

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This paper cites The elements of statistical learning.

Revisiting Bayesian Model Averaging in the Era of Foundation Models The elements of statistical learning

Reference 24

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This paper cites Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles

Reference 25

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This paper cites A decision-theoretic generalization of on-line learning and an application to boosting.

Revisiting Bayesian Model Averaging in the Era of Foundation Models A decision-theoretic generalization of on-line learning and an application to boosting

Reference 26

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This paper cites Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

Reference 27

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This paper cites Deep Ensembles for Low-Data Transfer Learning.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Deep Ensembles for Low-Data Transfer Learning

Reference 28

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This paper cites Being bayesian, even just a bit, fixes over- confidence in ReLU networks.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Being bayesian, even just a bit, fixes over- confidence in ReLU networks

Reference 29

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This paper cites Variational bayesian last layers.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Variational bayesian last layers

Reference 30

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This paper cites Do ImageNet Classifiers Generalize to ImageNet?.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Do ImageNet Classifiers Generalize to ImageNet?

Reference 31

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This paper cites Natural Adversarial Examples.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Natural Adversarial Examples

Reference 32

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Revisiting Bayesian Model Averaging in the Era of Foundation Models Learning robust global representations by penalizing local predictive power

Reference 33

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Revisiting Bayesian Model Averaging in the Era of Foundation Models Objectnet: A large-scale bias-controlled dataset for pushing the limits of object recognition models

Reference 34

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This paper cites The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization.

Revisiting Bayesian Model Averaging in the Era of Foundation Models The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization

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Revisiting Bayesian Model Averaging in the Era of Foundation Models Unresolved cited work

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Revisiting Bayesian Model Averaging in the Era of Foundation Models Ehinger, Aude Oliva, and Antonio Torralba

Reference 37

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Revisiting Bayesian Model Averaging in the Era of Foundation Models Automated flower classification over a large number of classes

Reference 38

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Revisiting Bayesian Model Averaging in the Era of Foundation Models Unresolved cited work

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Revisiting Bayesian Model Averaging in the Era of Foundation Models GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

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Revisiting Bayesian Model Averaging in the Era of Foundation Models Automatically constructing a corpus of sentential paraphrases

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Revisiting Bayesian Model Averaging in the Era of Foundation Models The pascal recognising textual entailment challenge

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Revisiting Bayesian Model Averaging in the Era of Foundation Models The second pascal recognising textual entailment challenge

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Revisiting Bayesian Model Averaging in the Era of Foundation Models The third pascal recognizing textual entailment challenge

Reference 44

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Revisiting Bayesian Model Averaging in the Era of Foundation Models The fifth pascal recognizing textual entailment challenge

Reference 45

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Revisiting Bayesian Model Averaging in the Era of Foundation Models Unresolved cited work

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Revisiting Bayesian Model Averaging in the Era of Foundation Models Recursive deep models for semantic compositionality over a sentiment treebank

Reference 47

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Revisiting Bayesian Model Averaging in the Era of Foundation Models Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping

Reference 48

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Revisiting Bayesian Model Averaging in the Era of Foundation Models Comparison of the predicted and observed secondary structure of t4 phage lysozyme

Reference 49

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Revisiting Bayesian Model Averaging in the Era of Foundation Models BERT: Pre-training of deep bidirectional transformers for language understanding

Reference 50

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Revisiting Bayesian Model Averaging in the Era of Foundation Models Unresolved cited work

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This paper cites Merging models with fisher-weighted averaging.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Merging models with fisher-weighted averaging

Reference 52

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Revisiting Bayesian Model Averaging in the Era of Foundation Models Unresolved cited work

Reference 53

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Revisiting Bayesian Model Averaging in the Era of Foundation Models N M MX n=1 CX c=1 yc n

Reference 54

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This paper cites Learning Robust Global Representations by Penalizing Local Predictive Power.

Revisiting Bayesian Model Averaging in the Era of Foundation Models Learning Robust Global Representations by Penalizing Local Predictive Power

Reference 2019

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