20 papers
Link prediction on multi-relational graphs from an influence propagation perspective
Zidu Yin, Yuankai Qi, Dong Gong +3
Predicting the existence and type of links (edges) between nodes in a multi-relational graph is key for applications from social interaction prediction to knowledge relationship id…
Feature-Space Bayesian Adversarial Learning Improved Malware Detector Robustness
Bao Gia Doan, Shuiqiao Yang, Paul Montague +6
We present a new algorithm to train a robust malware detector. Modern malware detectors rely on machine learning algorithms. Now, the adversarial objective is to devise alterations…
Multi-Hypothesis Test-Time Adaptation to Mitigate Underspecification
Afshar Shamsi, Xiao-Yu Guo, Hamid Alinejad-Rokny +3
Test-Time Adaptation (TTA) seeks to improve model robustness under distribution shifts by adapting parameters using unlabeled target data. However, in the absence of supervision, e…
Learning Latent Dynamical Causal Processes for Single-Cell Perturbation Prediction
Wenkang Jiang, Yuhang Liu, Erdun Gao +3
Single-cell perturbation prediction aims to infer how cells respond to unseen interventions and to achieve out-of-distribution (OOD) generalization, providing a computational route…
What Makes a Representation Good for Single-Cell Perturbation Prediction?
Wenkang Jiang, Yuhang Liu, Yichao Cai +5
Single-cell perturbation modeling is fundamental for understanding and predicting cellular responses to genetic perturbations. However, existing approaches, from causal representat…
Dual Strategies for Test-Time Adaptation
Nam Nguyen Phuong, Duc Nguyen The Minh, Phi Le Nguyen +2
Conventional test-time adaptation (TTA) approaches typically adapt the model using only a small fraction of test samples, often those with low-entropy predictions, thereby failing…