23 citations · 33 across the 8 of their papers we have counts for
8 papers
OmniGenBench: A Modular Platform for Reproducible Genomic Foundation Models Benchmarking
Heng Yang, Jack Cole, Yuan Li +3
The code of nature, embedded in DNA and RNA genomes since the origin of life, holds immense potential to impact both humans and ecosystems through genome modeling. Genomic Foundati…
Bridging Sequence-Structure Alignment in RNA Foundation Models
Heng Yang, Renzhi Chen, Ke Li
The alignment between RNA sequences and structures in foundation models (FMs) has yet to be thoroughly investigated. Existing FMs have struggled to establish sequence-structure ali…
A Data-Driven Evolutionary Transfer Optimization for Expensive Problems in Dynamic Environments
Ke Li, Renzhi Chen, Xin Yao
Many real-world problems are usually computationally costly and the objective functions evolve over time. Data-driven, a.k.a. surrogate-assisted, evolutionary optimization has been…
Data-Driven Evolutionary Multi-Objective Optimization Based on Multiple-Gradient Descent for Disconnected Pareto Fronts
Renzhi Chen, Ke Li
Data-driven evolutionary multi-objective optimization (EMO) has been recognized as an effective approach for multi-objective optimization problems with expensive objective function…
Batched Data-Driven Evolutionary Multi-Objective Optimization Based on Manifold Interpolation
Ke Li, Renzhi Chen
Multi-objective optimization problems are ubiquitous in real-world science, engineering and design optimization problems. It is not uncommon that the objective functions are as a b…
Interactive Decomposition Multi-Objective Optimization via Progressively Learned Value Functions
Ke Li, Renzhi Chen, Dragan Savic +1
Decomposition has become an increasingly popular technique for evolutionary multi-objective optimization (EMO). A decomposition-based EMO algorithm is usually designed to approxima…
Two-Archive Evolutionary Algorithm for Constrained Multi-Objective Optimization
Ke Li, Renzhi Chen, Guangtao Fu +1
When solving constrained multi-objective optimization problems, an important issue is how to balance convergence, diversity and feasibility simultaneously. To address this issue, t…
Dynamic Multi-Objectives Optimization with a Changing Number of Objectives
Renzhi Chen, Ke Li, Xin Yao
Existing studies on dynamic multi-objective optimization focus on problems with time-dependent objective functions, while the ones with a changing number of objectives have rarely…