Search Results for author:
Found 9 papers, 5 papers with code
Unsupervised Graph Neural Architecture Search with Disentangled Self-supervision
To address the challenge, we propose a novel Disentangled Self-supervised Graph Neural Architecture Search (DSGAS) model, which is able to discover the optimal architectures capturing various latent graph factors in a self-supervised fashion based on unlabeled graph data.
Membership Inference Attacks and Generalization: A Causal Perspective
Our causal models also show a new connection between generalization and MI attacks via their shared causal factors.
Quantitative Verification of Neural Networks And its Security Applications
Neural networks are increasingly employed in safety-critical domains.
THUMT: An Open Source Toolkit for Neural Machine Translation
This paper introduces THUMT, an open-source toolkit for neural machine translation (NMT) developed by the Natural Language Processing Group at Tsinghua University.
Neural Headline Generation with Sentence-wise Optimization
Recently, neural models have been proposed for headline generation by learning to map documents to headlines with recurrent neural networks.
Agreement-based Joint Training for Bidirectional Attention-based Neural Machine Translation
The attentional mechanism has proven to be effective in improving end-to-end neural machine translation.
Minimum Risk Training for Neural Machine Translation
We propose minimum risk training for end-to-end neural machine translation.
