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Modeling Uncertainty by Learning a Hierarchy of Deep Neural Connections (NeurIPS 2019)
Approximate Inference in Bayesian Deep Learning (NeurIPS 2021): Presentations by Competition Winners
[DeepBayes2019]: Day 1, Opening remarks
Bayesian Deep Learning
Yee Whye Teh: On Bayesian Deep Learning and Deep Bayesian Learning (NIPS 2017 Keynote)
BITESIZE | The Why & How of Bayesian Deep Learning, with Vincent Fortuin
#150 Fast Bayesian Deep Learning, with David Rügamer, Emanuel Sommer & Jakob Robnik
NeurIPS 2021: Laplace Redux -- Effortless Bayesian Deep Learning
DLRLSS 2019 - Bayesian Deep Learning - Roger Grosse
Yoshua Bengio | From System 1 Deep Learning to System 2 Deep Learning | NeurIPS 2019
Modeling Uncertainty by Learning A Hierarchy of Deep Neural Connections (NeurIPS 2019)
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Last Updated: October 3, 2026
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If you would to support the channel, please join the membership: youtube.com/c/AIPursuit/join to the ... If you enjoyed this video feel free to and ; also you can the for notifications! If you would to support ... This short video summarizes our Neural networks are the backbone of Presentations by the winners of the Slides: github.com/bayesgroup/deepbayes- Breiman Lecture by Yee Whye Teh on This conversation delves into the intricacies of Community-driven tools are vital for advancing Roger Grosse speaks at DLRL Summer School with his lecture on Slides: iro.umontreal.ca/~bengioy/ Raanan Yehezkel Rohekar, Research Scientist, Intel AI Week Yuval Ne'eman Workshop for Science, Technology and Security Tel ...