Multi-fidelity Monte Carlo: a pseudo-marginal approach

von Cai, Diana
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 28 of 50 (2023)

ON WARM-STARTING NEURAL NETWORK TRAINING

von Ash, Jordan
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 5 of 27 (2021)

Slice Sampling Reparameterization Gradients

von Zoltowski, David
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 28 of 36 (2022)

Patterns of scalable Bayesian inference

von Angelino, Elaine
Veröffentlicht 2016

Amortized Synthesis of Constrained Configurations Using a Differentiable Surrogate

von Sun, Xingyuan
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 23 of 36 (2022)

AMORTIZED FINITE ELEMENT ANALYSIS FOR FAST PDE-CONSTRAINED OPTIMIZATION

von Xue, Tianju
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 14 of 15 (2021)

TASK-AGNOSTIC AMORTIZED INFERENCE OF GAUSSIAN PROCESS HYPERPARAMETERS

von Liu, Sulin
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 26 of 27 (2021)

LEARNING COMPOSABLE ENERGY SURROGATES FOR PDE ORDER REDUCTION

von Beatson, Alex
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 1 of 27 (2021)

DISCRETE OBJECT GENERATION WITH REVERSIBLE INDUCTIVE CONSTRUCTION

von Seff, Ari
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 13 of 20 (2020)

ACTIVE MULTI-FIDELITY BAYESIAN ONLINE CHANGEPOINT DETECTION

von Gundersen, Gregory W.
Veröffentlicht in Conference on Uncertainty in Artificial Intelligence (37. : 2021 : Online) 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021) ; Part 3 of 3 (2022)

Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability

von Ghosh, Dibya
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 31 of 36 (2022)