影响力指数
论文质量、代表作、近期表现、广度与样本量置信度综合计算
15.25/100
超过 46.4%
全站排名 #34,486
发表论文3 篇
平均评分
年均产出3.0 篇/年
Umberto Michieli
研究方向
Model Compression · Semantic Segmentation · Continual Learning · Federated Learning · Domain Adaptation
16
Brain network science modelling of sparse neural networks enables Transformers and LLMs to perform as fully connected
NeurIPS 2025Poster
27
Adaptive Cannistraci-Hebb Network Automata Modelling of Complex Networks for Path-based Link Prediction
NeurIPS 2025Poster
三作23
RAC-LoRA: A Theoretical Optimization Framework for Low-Rank Adaptation
ICLR 2025Rejected
二作