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Found 5 papers, 2 papers with code
Adaptive Patching for High-resolution Image Segmentation with Transformers
For high-resolution images, e. g. microscopic pathology images, the quadratic compute and memory cost prohibits the use of an attention-based model, if we are to use smaller patch sizes that are favorable in segmentation.
Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules
Our results show that a subgraph-level tokenizer and a sufficiently expressive decoder with remask decoding have a large impact on the encoder's representation learning.
ReLM: Leveraging Language Models for Enhanced Chemical Reaction Prediction
Predicting chemical reactions, a fundamental challenge in chemistry, involves forecasting the resulting products from a given reaction process.
Accelerating the Evolutionary Algorithms by Gaussian Process Regression with $ε$-greedy acquisition function
Based on this hypothesis, in each generation of optimization, we replace the worst individual in Evolutionary Algorithms (EAs) with the elite individual to participate in the evolution process.
Accelerating the Genetic Algorithm for Large-scale Traveling Salesman Problems by Cooperative Coevolutionary Pointer Network with Reinforcement Learning
In this paper, we propose a two-stage optimization strategy for solving the Large-scale Traveling Salesman Problems (LSTSPs) named CCPNRL-GA. First, we hypothesize that the participation of a well-performed individual as an elite can accelerate the convergence of optimization.
