STATISTICALLY ROBUST NEURAL NETWORK CLASSIFICATION

von Wang, Benjie
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)

PROBABILISTIC PROGRAMS WITH STOCHASTIC CONDITIONING

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

ACTIVE TESTING: SAMPLE-EFFICIENT MODEL EVALUATION

von KOSSEN, JANNIK
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 8 of 16 (2022)

DEEP ADAPTIVE DESIGN: AMORTIZING SEQUENTIAL BAYESIAN EXPERIMENTAL DESIGN

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

DIVIDE, CONQUER, AND COMBINE: A NEW INFERENCE STRATEGY FOR PROBABILISTIC PROGRAMS WITH STOCHASTIC SUPPORT

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

ON SIGNAL-TO-NOISE RATIO ISSUES IN VARIATIONAL INFERENCE FOR DEEP GAUSSIAN PROCESSES

von RUDNER, TIM G. J.
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 12 of 16 (2022)