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07/17/2023
Learning for Counterfactual Fairness from Observational Data
Fairness-aware machine learning has attracted a surge of attention in ma...
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06/05/2023
Enhance Diffusion to Improve Robust Generalization
Deep neural networks are susceptible to human imperceptible adversarial ...
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11/29/2022
Understanding and Enhancing Robustness of Concept-based Models
Rising usage of deep neural networks to perform decision making in criti...
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10/16/2022
CLEAR: Generative Counterfactual Explanations on Graphs
Counterfactual explanations promote explainability in machine learning m...
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01/10/2022
Learning Fair Node Representations with Graph Counterfactual Fairness
Fair machine learning aims to mitigate the biases of model predictions a...
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05/17/2021
HetMAML: Task-Heterogeneous Model-Agnostic Meta-Learning for Few-Shot Learning Across Modalities
Most of existing gradient-based meta-learning approaches to few-shot lea...
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02/05/2020
A Survey on Causal Inference
Causal inference is a critical research topic across many domains, such ...
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06/03/2019
Incorporating Biological Knowledge with Factor Graph Neural Network for Interpretable Deep Learning
While deep learning has achieved great success in many fields, one commo...
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09/06/2018
Multi-view Factorization AutoEncoder with Network Constraints for Multi-omic Integrative Analysis
Multi-omic data provides multiple views of the same patients. Integrativ...
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05/22/2018