most citedMIMIC: A Generative Multimodal Foundation Model for Biomolecules

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.AI2026

Protein Design with Agent Rosetta: A Case Study for Specialized Scientific Agents

Jacopo Teneggi, S. M. Bargeen A. Turzo, Tanya Marwah +4

Large language models (LLMs) are capable of emulating reasoning and using tools, creating opportunities for autonomous agents that execute complex scientific tasks. Protein design…

cs.AI20261 cited

MIMIC: A Generative Multimodal Foundation Model for Biomolecules

Siavash Golkar, Jake Kovalic, Irina Espejo Morales +28

Biological function emerges from coupled constraints across sequence, structure, regulation, evolution, and cellular context, yet most foundation models in biology are trained with…

cs.ET2026

Playing Dice with the Universe: Programming Quantum Computers to Play Traditional Games

Tristan Zaborniak, Vikram Khipple Mulligan

The challenge of programming classical computers to play traditional, competitive games against human players has helped to advance classical hardware and software. Quantum compute…

quant-ph2026

Qubit-efficient and gate-efficient encodings of graph partitioning problems for quantum optimization

Tristan Zaborniak, Prashanti Priya Angara, Vikram Khipple Mulligan +2

We introduce a qubit- and gate-efficient higher-order unconstrained binary optimization (HUBO) encoding for graph partitioning problems requiring label-count minimization. This wid…

cs.ET2026

Entangled happily ever after: Wedding reception seating mapped to classical and quantum optimizers

Karie A. Nicholas, Vikram Khipple Mulligan

Although optimization is one of the most promising applications of quantum computers, the development of effective optimization strategies requires real-world test cases. When plan…