53 citations · 87 across the 6 of their papers we have counts for
7 papers
Training self-supervised peptide sequence models on artificially chopped proteins
Gil Sadeh, Zichen Wang, Jasleen Grewal +2
Representation learning for proteins has primarily focused on the global understanding of protein sequences regardless of their length. However, shorter proteins (known as peptides…
Robust posterior inference when statistically emulating forward simulations
Grigor Aslanyan, Richard Easther, Nathan Musoke +1
Scientific analyses often rely on slow, but accurate forward models for observable data conditioned on known model parameters. While various emulation schemes exist to approximate…
Discovering Invariances in Healthcare Neural Networks
Mohammad Taha Bahadori, Layne C. Price
We study the invariance characteristics of pre-trained predictive models by empirically learning transformations on the input that leave the prediction function approximately uncha…
Estimating Cosmological Parameters from the Dark Matter Distribution
Siamak Ravanbakhsh, Junier Oliva, Sebastien Fromenteau +4
A grand challenge of the 21st century cosmology is to accurately estimate the cosmological parameters of our Universe. A major approach to estimating the cosmological parameters is…
Effect of reheating on predictions following multiple-field inflation
Selim C. Hotinli, Jonathan Frazer, Andrew H. Jaffe +3
We study the sensitivity of cosmological observables to the reheating phase following inflation driven by many scalar fields. We describe a method which allows semi-analytic treatm…
The Spectrum of the Axion Dark Sector
Matthew J. Stott, David J. E. Marsh, Chakrit Pongkitivanichkul +2
Axions arise in many theoretical extensions of the Standard Model of particle physics, in particular the "string axiverse". If the axion masses, , and (effective) decay consta…