( en | de | ru )

 

Disambiguation

From post

копироватьудалитьдобавить публикацию в буфер
URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks

, , , и . (2020)cite arxiv:2007.04466Comment: Presented at the ICML 2020 Workshop on Uncertainty and Robustness in Deep Learning.

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed.

Birgit Cobbers

John Ernest Cobbina

Joanna Cobb Biermann

James Edward Cobbah

Christian Cobbers

 

Другие публикации лиц с тем же именем

URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks, , , и . (2020)cite arxiv:2007.04466Comment: Presented at the ICML 2020 Workshop on Uncertainty and Robustness in Deep Learning.Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus., , , и . KDD, стр. 1254-1262. ACM, (2018)On Sequential Bayesian Inference for Continual Learning., , , , и . CoRR, (2023)URSABench: A System for Comprehensive Benchmarking of Bayesian Deep Neural Network Models and Inference methods., , , , , и . MLSys, mlsys.org, (2022)Learning from lions: inferring the utility of agents from their trajectories., , и . CoRR, (2017)BayesOpt Adversarial Attack., , , и . ICLR, OpenReview.net, (2020)Optimising Worlds to Evaluate and Influence Reinforcement Learning Agents., , , и . AAMAS, стр. 1943-1945. International Foundation for Autonomous Agents and Multiagent Systems, (2019)Scaling Hamiltonian Monte Carlo inference for Bayesian neural networks with symmetric splitting., и . UAI, том 161 из Proceedings of Machine Learning Research, стр. 675-685. AUAI Press, (2021)hamiltorch: A PyTorch-based library for Hamiltonian Monte Carlo.. CPS-IoT Week Workshops, стр. 114-115. ACM, (2023)Challenges and Opportunities in Neuro-Symbolic Composition of Foundation Models., , , , и . MILCOM, стр. 156-161. IEEE, (2023)