Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes

von Benton, Gregory
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 3 of 33 (2023)

A PRACTICAL METHOD FOR CONSTRUCTING EQUIVARIANT MULTILAYER PERCEPTRONS FOR ARBITRARY MATRIX GROUPS

von FINZI, MARC
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 5 of 16 (2022)

Low-Precision Stochastic Gradient Langevin Dynamics

von Zhang, Ruqi
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 32 of 33 (2023)

SEMI-SUPERVISED LEARNING WITH NORMALIZING FLOWS

von Izmailov, Pavel
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 6 of 15 (2021)

WHAT ARE BAYESIAN NEURAL NETWORK POSTERIORS REALLY LIKE?

von IZMAILOV, PAVEL
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 6 of 16 (2022)

SCALABLE VARIATIONAL GAUSSIAN PROCESSES VIA HARMONIC KERNEL DECOMPOSITION

von SUN, SHENGYANG
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 13 of 16 (2022)

LOSS SURFACE SIMPLEXES FOR MODE CONNECTING VOLUMES AND FAST ENSEMBLING

von BENTON, GREGORY W.
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 2 of 16 (2022)

Bayesian Model Selection, the Marginal Likelihood, and Generalization

von Lotfi, Sanae
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 18 of 33 (2023)

SKIING ON SIMPLICES: KERNEL INTERPOLATION ON THE PERMUTOHEDRAL LATTICE FOR SCALABLE GAUSSIAN PROCESSES

von KAPOOR, SANYAM
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 7 of 16 (2022)

A SIMPLE BASELINE FOR BAYESIAN UNCERTAINTY IN DEEP LEARNING

von Maddox, Wesley J.
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 17 of 20 (2020)

Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders

von Stanton, Samuel
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 35 of 33 (2023)