Homomorphic binary tree. by Jianhua He (341366)

Binary contingency table. by Lu Xiao (314030)

Face recognition algorithm flow based on the PCA. by Na Lin (69470)

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.…”

Diversity and specificity of lipid patterns in basal soil food web resources by Jakob Kühn (7288466)

“…In marine environments, multivariate optimization models (Quantitative Fatty Acid Signature Analysis) and Bayesian approaches (source-tracking algorithm) were established to predict the proportion of predator diets using lipids as tracers. …”

Minisymposterium: Muq-Hippylib: A Bayesian Inference Software Framework Integrating Data with Complex Predictive Models under Uncertainty by Ki-Tae Kim (10184066)

“…In this poster, we present an extensible software framework MUQ-hIPPYlib that overcomes this hurdle by providing unprecedented access to state-of-the-art algorithms for Bayesian inverse problems. MUQ provides a spectrum of powerful Bayesian inversion models and algorithms, but expects forward models to come equipped with gradients/Hessians to permit large-scale solution. hIPPYlib implements powerful large-scale gradient/Hessian-based solvers in an environment that can automatically generate needed derivatives, but it lacks full Bayesian capabilities. …”

SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion by Omar Ghattas (4387300)

“…MUQ provides a spectrum of powerful Bayesian inversion models and algorithms, but expects forward models to come equipped with gradients/Hessians to permit large-scale solution. hIPPYlib implements powerful large-scale gradient/Hessian-based solvers in an environment that can automatically generate needed derivatives, but it lacks full Bayesian capabilities. …”

SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion by Umberto Villa (8400192)

“…MUQ provides a spectrum of powerful Bayesian inversion models and algorithms, but expects forward models to come equipped with gradients/Hessians to permit large-scale solution. hIPPYlib implements powerful large-scale gradient/Hessian-based solvers in an environment that can automatically generate needed derivatives, but it lacks full Bayesian capabilities. …”

Data_Sheet_1_Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer.pdf by Maliheh Aramon (6557906)

“…Our results suggest an improved scaling over the other algorithms for fully connected problems of average difficulty with bimodal disorder. …”

Image1_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF by Sizhuo Yu (11429743)

“…Its current hardware implementation relies on D-Wave’s Quantum Processing Units, which are limited in terms of number of qubits and architecture while being restricted to solving quadratic unconstrained binary optimization (QUBO) problems. …”

Image3_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF by Sizhuo Yu (11429743)

“…Its current hardware implementation relies on D-Wave’s Quantum Processing Units, which are limited in terms of number of qubits and architecture while being restricted to solving quadratic unconstrained binary optimization (QUBO) problems. …”

Image2_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF by Sizhuo Yu (11429743)

“…Its current hardware implementation relies on D-Wave’s Quantum Processing Units, which are limited in terms of number of qubits and architecture while being restricted to solving quadratic unconstrained binary optimization (QUBO) problems. …”

DataSheet1_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.pdf by Sizhuo Yu (11429743)

“…Its current hardware implementation relies on D-Wave’s Quantum Processing Units, which are limited in terms of number of qubits and architecture while being restricted to solving quadratic unconstrained binary optimization (QUBO) problems. …”