3 citations · 5 across the 5 of their papers we have counts for
5 papers
Large Language Model is Secretly a Protein Sequence Optimizer
Yinkai Wang, Jiaxing He, Yuanqi Du +5
We consider the protein sequence engineering problem, which aims to find protein sequences with high fitness levels, starting from a given wild-type sequence. Directed evolution ha…
MHub: Unlocking the Potential of Machine Learning for Materials Discovery
Yuanqi Du, Yingheng Wang, Yining Huang +6
We introduce MHub, a toolkit for advancing machine learning in materials discovery. Machine learning has achieved remarkable progress in modeling molecular structures, especial…
MCTensor: A High-Precision Deep Learning Library with Multi-Component Floating-Point
Tao Yu, Wentao Guo, Jianan Canal Li +2
In this paper, we introduce MCTensor, a library based on PyTorch for providing general-purpose and high-precision arithmetic for DL training. MCTensor is used in the same way as Py…
Cyclical Kernel Adaptive Metropolis
Jianan Canal Li, Yimeng Zeng, Wentao Guo
We propose cKAM, cyclical Kernel Adaptive Metropolis, which incorporates a cyclical stepsize scheme to allow control for exploration and sampling. We show that on a crafted bimodal…
A global quadratic speed-up for computing the principal eigenvalue of Perron-like operators
Dong Li, Jianan Li
We consider a new algorithm in light of the min-max Collatz-Wielandt formalism to compute the principal eigenvalue and the eigenvector (eigen-function) for a class of positive Perr…