"Importance Weighted Hierarchical Variational Inference"
By Artem Sobolev and Dmitry Vetrov: https://arxiv.org/abs/1905.03290
Talk: https://youtu.be/pdSu7XfGhHw
#Bayesian #MachineLearning #VariationalInference
By Artem Sobolev and Dmitry Vetrov: https://arxiv.org/abs/1905.03290
Talk: https://youtu.be/pdSu7XfGhHw
#Bayesian #MachineLearning #VariationalInference
ArviZ: Exploratory analysis of Bayesian models
Includes functions for posterior analysis, sample diagnostics, model checking, and comparison: https://arviz-devs.github.io/arviz/
#ArtificialIntelligence #Bayesian #BayesianInference #MachineLearning #Python
Includes functions for posterior analysis, sample diagnostics, model checking, and comparison: https://arviz-devs.github.io/arviz/
#ArtificialIntelligence #Bayesian #BayesianInference #MachineLearning #Python
ArviZ: Exploratory analysis of Bayesian models
Includes functions for posterior analysis, sample diagnostics, model checking, and comparison: https://arviz-devs.github.io/arviz/
#ArtificialIntelligence #Bayesian #BayesianInference #MachineLearning #Python
Includes functions for posterior analysis, sample diagnostics, model checking, and comparison: https://arviz-devs.github.io/arviz/
#ArtificialIntelligence #Bayesian #BayesianInference #MachineLearning #Python
Practical Deep Learning with Bayesian Principles
Osawa et al.: https://arxiv.org/pdf/1906.02506.pdf
#Bayesian #DeepLearning #PyTorch #VariationalInference
Osawa et al.: https://arxiv.org/pdf/1906.02506.pdf
#Bayesian #DeepLearning #PyTorch #VariationalInference
The Functional Neural Process
Louizos et al.: https://arxiv.org/abs/1906.08324
#ArtificialIntelligence #Bayesian #MachineLearning
Louizos et al.: https://arxiv.org/abs/1906.08324
#ArtificialIntelligence #Bayesian #MachineLearning
Pathologies of Factorised Gaussian and MC Dropout Posteriors in Bayesian Neural Networks
Foong et al.: https://arxiv.org/abs/1909.00719
#Bayesian #NeuralNetworks #MachineLearning
Foong et al.: https://arxiv.org/abs/1909.00719
#Bayesian #NeuralNetworks #MachineLearning
BoTorch: Programmable Bayesian Optimization in PyTorch
Balandat et al.: https://arxiv.org/abs/1910.06403
Code: https://github.com/pytorch/botorch
#MachineLearning #Bayesian #PyTorch
Balandat et al.: https://arxiv.org/abs/1910.06403
Code: https://github.com/pytorch/botorch
#MachineLearning #Bayesian #PyTorch
Materials of the Summer school on Deep learning and Bayesian methods 2019
GitHub : https://github.com/bayesgroup/deepbayes-2019
#ArtificialIntelligence #DeepLearning #Bayesian
GitHub : https://github.com/bayesgroup/deepbayes-2019
#ArtificialIntelligence #DeepLearning #Bayesian
Bayesian Deep Learning Benchmarks
GitHub, by the Oxford Applied and Theoretical Machine Learning group : https://github.com/OATML/bdl-benchmarks
#Bayesian #DeepLearning #Benchmarks
GitHub, by the Oxford Applied and Theoretical Machine Learning group : https://github.com/OATML/bdl-benchmarks
#Bayesian #DeepLearning #Benchmarks
GitHub
GitHub - OATML/bdl-benchmarks: Bayesian Deep Learning Benchmarks
Bayesian Deep Learning Benchmarks. Contribute to OATML/bdl-benchmarks development by creating an account on GitHub.
Neural Density Estimation and Likelihood-free Inference
George Papamakarios : https://arxiv.org/pdf/1910.13233.pdf
#Bayesian #NeuralDensityEstimation #Inference
George Papamakarios : https://arxiv.org/pdf/1910.13233.pdf
#Bayesian #NeuralDensityEstimation #Inference
Bayesian Deep Learning - NeurIPS 2019 Workshop
Friday, December 13, 2019 — Vancouver Convention Center, Vancouver, Canada : http://bayesiandeeplearning.org
#bayesian #deeplearning #neurips2019
Friday, December 13, 2019 — Vancouver Convention Center, Vancouver, Canada : http://bayesiandeeplearning.org
#bayesian #deeplearning #neurips2019
bayesiandeeplearning.org
Bayesian Deep Learning Workshop | NeurIPS 2021
Bayesian Deep Learning Workshop at NeurIPS 2021 — Tuesday, December 14, 2021, Virtual.
Bayesian Deep Learning Benchmarks
Oxford Applied and Theoretical Machine Learning Group : https://github.com/OATML/bdl-benchmarks
#Bayesian #Benchmark #DeepLearning
Oxford Applied and Theoretical Machine Learning Group : https://github.com/OATML/bdl-benchmarks
#Bayesian #Benchmark #DeepLearning
GitHub
GitHub - OATML/bdl-benchmarks: Bayesian Deep Learning Benchmarks
Bayesian Deep Learning Benchmarks. Contribute to OATML/bdl-benchmarks development by creating an account on GitHub.
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search
White et al.: https://arxiv.org/abs/1910.11858
#Bayesian #Optimization #NeuralArchitectureSearch
White et al.: https://arxiv.org/abs/1910.11858
#Bayesian #Optimization #NeuralArchitectureSearch
Bayesian Deep Learning Benchmarks
Oxford Applied and Theoretical Machine Learning Group : https://github.com/OATML/bdl-benchmarks
#Bayesian #Benchmark #DeepLearning
Oxford Applied and Theoretical Machine Learning Group : https://github.com/OATML/bdl-benchmarks
#Bayesian #Benchmark #DeepLearning
GitHub
GitHub - OATML/bdl-benchmarks: Bayesian Deep Learning Benchmarks
Bayesian Deep Learning Benchmarks. Contribute to OATML/bdl-benchmarks development by creating an account on GitHub.
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search
White et al.: https://arxiv.org/abs/1910.11858
#Bayesian #Optimization #NeuralArchitectureSearch
White et al.: https://arxiv.org/abs/1910.11858
#Bayesian #Optimization #NeuralArchitectureSearch
arXiv.org
BANANAS: Bayesian Optimization with Neural Architectures for...
Over the past half-decade, many methods have been considered for neural architecture search (NAS). Bayesian optimization (BO), which has long had success in hyperparameter optimization, has...
Bayesian Deep Learning Benchmarks
Oxford Applied and Theoretical Machine Learning Group : https://github.com/OATML/bdl-benchmarks
#Bayesian #Benchmark #DeepLearning
Oxford Applied and Theoretical Machine Learning Group : https://github.com/OATML/bdl-benchmarks
#Bayesian #Benchmark #DeepLearning
GitHub
GitHub - OATML/bdl-benchmarks: Bayesian Deep Learning Benchmarks
Bayesian Deep Learning Benchmarks. Contribute to OATML/bdl-benchmarks development by creating an account on GitHub.
The Case for Bayesian Deep Learning
Andrew Gordon Wilson: https://arxiv.org/abs/2001.10995
#Bayesian #DeepLearning #MachineLearning
Andrew Gordon Wilson: https://arxiv.org/abs/2001.10995
#Bayesian #DeepLearning #MachineLearning
Bayesian Deep Learning and a Probabilistic Perspective of Generalization
Andrew Gordon Wilson, Pavel Izmailov : https://arxiv.org/abs/2002.08791
#Artificialintelligence #Bayesian #DeepLearning
Andrew Gordon Wilson, Pavel Izmailov : https://arxiv.org/abs/2002.08791
#Artificialintelligence #Bayesian #DeepLearning