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
-/100
发表论文3 篇
平均评分
年均产出3.0 篇/年
Emanuele Ballarin
研究方向
Computational Neuroscience · Generative Modelling · Deep Learning · Adversarially-Robust Machine Learning · Artificial Neural Networks
16
Carefully Blending Adversarial Training and Purification Improves Adversarial Robustness
NeurIPS 2024Rejected
一作25
CARSO: Blending Adversarial Training and Purification Improves Adversarial Robustness
ICLR 2024Rejected
一作-
Emergent representations in networks trained with the Forward-Forward algorithm
ICLR 2024Withdrawn
三作