4 papers
Jacobian-Based Interpretation of Nonlinear Neural Encoding Model
Xiaohui Gao, Haoran Yang, Yue Cheng +4
In recent years, the alignment between artificial neural network (ANN) embeddings and blood oxygenation level dependent (BOLD) responses in functional magnetic resonance imaging (f…
LCGC: Learning from Consistency Gradient Conflicting for Class-Imbalanced Semi-Supervised Debiasing
Weiwei Xing, Yue Cheng, Hongzhu Yi +5
Classifiers often learn to be biased corresponding to the class-imbalanced dataset, especially under the semi-supervised learning (SSL) set. While previous work tries to appropriat…
LinBridge: A Learnable Framework for Interpreting Nonlinear Neural Encoding Models
Xiaohui Gao, Yue Cheng, Peiyang Li +7
Neural encoding of artificial neural networks (ANNs) links their computational representations to brain responses, offering insights into how the brain processes information. Curre…
LOCAL: Learning with Orientation Matrix to Infer Causal Structure from Time Series Data
Jiajun Zhang, Boyang Qiang, Xiaoyu Guo +3
Discovering the underlying Directed Acyclic Graph (DAG) from time series observational data is highly challenging due to the dynamic nature and complex nonlinear interactions betwe…