Search Results for author:
Found 5 papers, 1 papers with code
Fair Multivariate Adaptive Regression Splines for Ensuring Equity and Transparency
In this paper, we propose a fair predictive model based on multivariate adaptive regression splines(MARS) that incorporates fairness measures in the learning process.
Learned Mappings for Targeted Free Energy Perturbation between Peptide Conformations
Targeted free energy perturbation uses an invertible mapping to promote configuration space overlap and the convergence of free energy estimates.
Sampling Constrained Continuous Probability Distributions: A Review
The problem of sampling constrained continuous distributions has frequently appeared in many machine/statistical learning models.
A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel
We propose a novel deterministic sampling method to approximate a target distribution $\rho^*$ by minimizing the kernel discrepancy, also known as the Maximum Mean Discrepancy (MMD).
Particle-based Energetic Variational Inference
Using the EVI framework, we can derive many existing Particle-based Variational Inference (ParVI) methods, including the popular Stein Variational Gradient Descent (SVGD) approach.
