From post

A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning

, , , и . (2021)cite arxiv:2110.01515Comment: Accepted as a survey article in IEEE TPAMI.

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.

 

Другие публикации лиц с тем же именем

A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning., , , и . IEEE Trans. Pattern Anal. Mach. Intell., 45 (2): 1353-1371 (2023)Ancestral Gumbel-Top-k Sampling for Sampling Without Replacement., , и . J. Mach. Learn. Res., (2020)Buy 4 REINFORCE Samples, Get a Baseline for Free!, , и . DeepRLStructPred@ICLR, OpenReview.net, (2019)PyVRP: A High-Performance VRP Solver Package., , и . INFORMS J. Comput., 36 (4): 943-955 (2024)Attention, Learn to Solve Routing Problems!, , и . ICLR (Poster), OpenReview.net, (2019)Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement., , и . ICML, том 97 из Proceedings of Machine Learning Research, стр. 3499-3508. PMLR, (2019)Hard choices: Children's understanding of the cost of action selection., , , , и . CogSci, стр. 671-6677. cognitivesciencesociety.org, (2019)Estimating Gradients for Discrete Random Variables by Sampling without Replacement., , и . ICLR, OpenReview.net, (2020)Toward a Rational and Mechanistic Account of Mental Effort, , , , , , и . Annual Review of Neuroscience, (июля 2017)A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning, , , и . (2021)cite arxiv:2110.01515Comment: Accepted as a survey article in IEEE TPAMI.