44 citations · 92 across the 7 of their papers we have counts for
7 papers
Is novelty predictable?
Clara Fannjiang, Jennifer Listgarten
Machine learning-based design has gained traction in the sciences, most notably in the design of small molecules, materials, and proteins, with societal implications spanning drug…
Prediction-Powered Inference
Anastasios N. Angelopoulos, Stephen Bates, Clara Fannjiang +2
Prediction-powered inference is a framework for performing valid statistical inference when an experimental dataset is supplemented with predictions from a machine-learning system.…
Conformal Prediction Under Feedback Covariate Shift for Biomolecular Design
Clara Fannjiang, Stephen Bates, Anastasios N. Angelopoulos +2
Many applications of machine learning methods involve an iterative protocol in which data are collected, a model is trained, and then outputs of that model are used to choose what…
Variational Refinement for Importance Sampling Using the Forward Kullback-Leibler Divergence
Ghassen Jerfel, Serena Wang, Clara Fannjiang +3
Variational Inference (VI) is a popular alternative to asymptotically exact sampling in Bayesian inference. Its main workhorse is optimization over a reverse Kullback-Leibler diver…
Autofocused oracles for model-based design
Clara Fannjiang, Jennifer Listgarten
Data-driven design is making headway into a number of application areas, including protein, small-molecule, and materials engineering. The design goal is to construct an object wit…
A view of Estimation of Distribution Algorithms through the lens of Expectation-Maximization
David H. Brookes, Akosua Busia, Clara Fannjiang +2
We show that a large class of Estimation of Distribution Algorithms, including, but not limited to, Covariance Matrix Adaption, can be written as a Monte Carlo Expectation-Maximiza…
Optimal Arrays for Compressed Sensing in Snapshot-Mode Radio Interferometry
Clara Fannjiang
Radio interferometry has always faced the problem of incomplete sampling of the Fourier plane. A possible remedy can be found in the promising new theory of compressed sensing (CS)…