Bayesian Bootstrap Spike-and-Slab LASSO by Lizhen Nie (12419334)

“…BB-SSL turns fast optimization into approximate posterior sampling. Beyond its scalability, we show that BB-SSL has a strong theoretical support. …”

Neuronized Priors for Bayesian Sparse Linear Regression by Minsuk Shin (5570855)

“…Theoretically, we provide specific conditions on the neuronized formulation to achieve the optimal posterior contraction rate, and show that a broadly applicable MCMC algorithm achieves an exponentially fast convergence rate under the neuronized formulation. …”

Bayesian Clustering via Fusing of Localized Densities by Alexander Dombowsky (20289372)

“…After defining a prior for the component parameters and weights, Markov chain Monte Carlo (MCMC) algorithms are commonly used to produce samples from the posterior distribution of the component labels. …”

Proximal MCMC for Bayesian Inference of Constrained and Regularized Estimation by Xinkai Zhou (9346175)

“…Originally introduced in the Bayesian imaging literature, ProxMCMC employs the Moreau-Yosida envelope for a smooth approximation of the total-variation regularization term, fixes variance and regularization strength parameters as constants, and uses the Langevin algorithm for the posterior sampling. …”

DataSheet1_Uncertainty quantified discovery of chemical reaction systems via Bayesian scientific machine learning.PDF by Emily Nieves (18123799)

“…To achieve this, we propose an algorithm which combines neural ODEs with a preconditioned stochastic gradient langevin descent (pSGLD) Bayesian framework, and ultimately performs posterior sampling on the neural network weights. …”

Adaptive Conditional Distribution Estimation with Bayesian Decision Tree Ensembles by Yinpu Li (12041379)

“…To fit our model, we propose a data augmentation algorithm which allows for existing BART samplers to be extended with minimal effort. …”

Results of network meta-analysis. by Kaiyu Zhang (198799)

“…Therefore, based on Bayesian algorithm, a network meta-analysis was conducted by us to make a comparison between different combination therapies of α-RBs and traditional Chinese medicine external therapy.…”

Results of network meta-analysis. by Kaiyu Zhang (198799)

“…Therefore, based on Bayesian algorithm, a network meta-analysis was conducted by us to make a comparison between different combination therapies of α-RBs and traditional Chinese medicine external therapy.…”

Results of network meta-analysis. by Kaiyu Zhang (198799)

“…Therefore, based on Bayesian algorithm, a network meta-analysis was conducted by us to make a comparison between different combination therapies of α-RBs and traditional Chinese medicine external therapy.…”

Results of network meta-analysis. by Kaiyu Zhang (198799)

“…Therefore, based on Bayesian algorithm, a network meta-analysis was conducted by us to make a comparison between different combination therapies of α-RBs and traditional Chinese medicine external therapy.…”

Study flowchart. by Kaiyu Zhang (198799)

“…Therefore, based on Bayesian algorithm, a network meta-analysis was conducted by us to make a comparison between different combination therapies of α-RBs and traditional Chinese medicine external therapy.…”

Risk of bias graph. by Kaiyu Zhang (198799)

“…Therefore, based on Bayesian algorithm, a network meta-analysis was conducted by us to make a comparison between different combination therapies of α-RBs and traditional Chinese medicine external therapy.…”

Results of network meta-analysis. by Kaiyu Zhang (198799)

“…Therefore, based on Bayesian algorithm, a network meta-analysis was conducted by us to make a comparison between different combination therapies of α-RBs and traditional Chinese medicine external therapy.…”

Characteristics of included studies. by Kaiyu Zhang (198799)

“…Therefore, based on Bayesian algorithm, a network meta-analysis was conducted by us to make a comparison between different combination therapies of α-RBs and traditional Chinese medicine external therapy.…”

DataSheet1_Biological Network Inference With GRASP: A Bayesian Network Structure Learning Method Using Adaptive Sequential Monte Carlo.docx by Kaixian Yu (2836709)

“…A double filtering strategy was first used for discovering the overall skeleton of the target BN. To search for the optimal network structures we designed an adaptive SMC (adSMC) algorithm to increase the quality and diversity of sampled networks which were further improved by a third stage to reclaim edges missed in the skeleton discovery step. …”

Data Sheet 1_A novel method for power transformer fault diagnosis considering imbalanced data samples.docx by Jun Chen (4238)

“…Hyperparameter tuning is achieved through the Bayesian optimization algorithm to identify the model parameter set that maximizes test set accuracy.…”

Data Sheet 2_Early stroke detection through machine learning in the prehospital setting.pdf by María Ríos Delgado (22004942)

Data Sheet 1_Early stroke detection through machine learning in the prehospital setting.pdf by María Ríos Delgado (22004942)

Table 1_Early stroke detection through machine learning in the prehospital setting.xlsx by María Ríos Delgado (22004942)

Application of ABC SMC to the fitting of the binary flip with cusp model. by Elena Camacho-Aguilar (10906327)