4 citations · 7 across the 4 of their papers we have counts for
6 papers
Differentiable RNA Secondary Structure Extraction for Deep Learning
Tyler Illman, Max Ward, Marcell Szikszai +1
Many deep learning approaches to RNA secondary structure prediction have recently been proposed. They typically output a weight matrix where is an arbitrary weight for…
General Purpose Inverse Design of Heterogeneous Finite-Sized Assemblies
Livia A. J. Guttieres, Ryan K. Krueger, Remi Drolet +1
Designing heterogeneous, self-assembling systems is a central challenge in soft matter and biology. We present a framework that uses gradient-based optimization to invert an analyt…
An AI system to help scientists write expert-level empirical software
Eser Aygün, Anastasiya Belyaeva, Gheorghe Comanici +39
The cycle of scientific discovery is frequently bottlenecked by the slow, manual creation of software to support computational experiments\cite{hannay2009how}. To address this, we…
Differentiable Folding for Nearest Neighbor Model Optimization
Ryan K. Krueger, Sharon Aviran, David H. Mathews +2
The Nearest Neighbor model is the thermodynamic model of RNA secondary structure formation and is a cornerstone of RNA structure prediction and sequence design.…
Fitting Coarse-Grained Models to Macroscopic Experimental Data via Automatic Differentiation
Ryan K. Krueger, Megan C. Engel, Ryan Hausen +1
Developing physics-based models for molecular simulation requires fitting many unknown parameters to diverse experimental datasets. Traditionally, this process is piecemeal and dif…
Tuning Colloidal Reactions
Ryan Krueger, Ella King, Michael Brenner
The precise control of complex reactions is critical for biological processes yet our inability to design for specific outcomes limits the development of synthetic analogues. Here,…