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
43.41/100
前 12%
全站排名 #7,749
发表论文8 篇
平均评分
年均产出2.7 篇/年
21
Intrinsic Benefits of Categorical Distributional Loss: Uncertainty-aware Regularized Exploration in Reinforcement Learning
NeurIPS 2025Poster
一作29
Principled Fast and Meta Knowledge Learners for Continual Reinforcement Learning
NeurIPS 2025Rejected
一作28
The Benefits of Being Categorical Distributional: Uncertainty-aware Regularized Exploration in Reinforcement Learning
ICLR 2025Rejected
一作