Results 31 to 40 of about 5,051,769 (292)
CoRR, 2022 Estimating an individual's potential outcomes under counterfactual treatments is a challenging task for traditional causal inference and supervised learning approaches when the outcome is high-dimensional (e.g. gene expressions, impulse responses, human faces) and covariates are relatively limited.
Wu, Yulun +5 more
openaire +2 more sources
IEEE Access, 2023 This paper proposes a model estimation method in offline Bayesian model-based reinforcement learning (MBRL). Learning a Bayes-adaptive Markov decision process (BAMDP) model using standard variational inference often suffers from poor predictive ...
Toru Hishinuma, Kei Senda
doaj +1 more source
VISinger: Variational Inference with Adversarial Learning for End-to-End Singing Voice Synthesis [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2021 In this paper, we propose VISinger, a complete end-to-end high-quality singing voice synthesis (SVS) system that directly generates singing audio from lyrics and musical score.
Yongmao Zhang +5 more
semanticscholar +1 more source
Dual Online Stein Variational Inference for Control and Dynamics [PDF]
Robotics: Science and Systems, 2021 Model predictive control (MPC) schemes have a proven track record for delivering aggressive and robust performance in many challenging control tasks, coping with nonlinear system dynamics, constraints, and observational noise.
Lucas Barcelos +5 more
semanticscholar +1 more source
A Design Methodology for Fault-Tolerant Neuromorphic Computing Using Bayesian Neural Network
Micromachines, 2023 Memristor crossbar arrays are a promising platform for neuromorphic computing. In practical scenarios, the synapse weights represented by the memristors for the underlying system are subject to process variations, in which the programmed weight when read
Di Gao, Xiaoru Xie, Dongxu Wei
doaj +1 more source
A Novel Anti-Jamming Technique for INS/GNSS Integration Based on Black Box Variational Inference
Applied Sciences, 2021 In this paper, a novel anti-jamming technique based on black box variational inference for INS/GNSS integration with time-varying measurement noise covariance matrices is presented. We proved that the time-varying measurement noise is more similar to the
Ping Dong, Jianhua Cheng, Liqiang Liu
doaj +1 more source
An Introduction to Variational Inference
CoRR, 2021 13 pages, 9 ...
Ankush Ganguly, Samuel W. F. Earp
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Collaborative filtering recommendation algorithm based on variational inference
International Journal of Crowd Science, 2020 PurposeThe purpose of this paper is to alleviate the problem of poor robustness and over-fitting caused by large-scale data in collaborative filtering recommendation algorithms.Design/methodology/approachInterpreting user behavior from the probabilistic ...
Kai Zheng +4 more
doaj +1 more source
An Out-of-Distribution Generalization Framework Based on Variational Backdoor Adjustment
Mathematics, 2023 In practical applications, learning models that can perform well even when the data distribution is different from the training set are essential and meaningful. Such problems are often referred to as out-of-distribution (OOD) generalization problems. In
Hang Su, Wei Wang
doaj +1 more source
Nonparametric variational inference [PDF]
CoRR, 2012 ICML2012
Samuel Gershman +2 more
openaire +2 more sources