1 citations · 1 across the 4 of their papers we have counts for
5 papers
Scalable Diffusion SBI for Compositional Inference under Simulator Misspecification
Vincent D. Zaballa, Elliot E. Hui
Simulation-based inference is challenging when many heterogeneous observations must be composed, hierarchical latent structure must be preserved, and the simulator is misspecified…
Optimizing Likelihoods via Mutual Information: Bridging Simulation-Based Inference and Bayesian Optimal Experimental Design
Vincent D. Zaballa, Elliot E. Hui
Simulation-based inference (SBI) is a method to perform inference on a variety of complex scientific models with challenging inference (inverse) problems. Bayesian Optimal Experime…
Systems-Structure-Based Drug Design
Vincent D. Zaballa, Elliot E. Hui
Recent advances in generative deep learning have transformed small molecule design, but most methods lack biological systems context, focusing narrowly on specific protein pockets.…
Reducing Uncertainty Through Mutual Information in Structural and Systems Biology
Vincent D. Zaballa, Elliot E. Hui
Systems biology models are useful models of complex biological systems that may require a large amount of experimental data to fit each model's parameters or to approximate a likel…
Approximation of Intractable Likelihood Functions in Systems Biology via Normalizing Flows
Vincent D. Zaballa, Elliot E. Hui
Systems biology relies on mathematical models that often involve complex and intractable likelihood functions, posing challenges for efficient inference and model selection. Genera…