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cs.LG2026
CoDiffGRN: Rethinking Gene Regulatory Network Inference via the BEELINE-KGC Benchmark and Co-evolutionary Discrete Diffusion
Jiaze Song, Runhao Zhao, Minghao Xu +2
Inferring gene regulatory networks (GRNs) from single-cell transcriptomic data is crucial for biological discovery, yet existing approaches suffer from a fundamental misalignment w…
cs.LG2024
Acceleration Algorithms in GNNs: A Survey
Lu Ma, Zeang Sheng, Xunkai Li +5
Graph Neural Networks (GNNs) have demonstrated effectiveness in various graph-based tasks. However, their inefficiency in training and inference presents challenges for scaling up…