150 citations · 415 across the 37 of their papers we have counts for
3 papers · 1 filter
Quantifying Model Uncertainty in Inverse Problems via Bayesian Deep Gradient Descent
Riccardo Barbano, Chen Zhang, Simon Arridge +1
Recent advances in reconstruction methods for inverse problems leverage powerful data-driven models, e.g., deep neural networks. These techniques have demonstrated state-of-the-art…
End-to-end Emotion-Cause Pair Extraction via Learning to Link
Haolin Song, Chen Zhang, Qiuchi Li +1
Emotion-cause pair extraction (ECPE), as an emergent natural language processing task, aims at jointly investigating emotions and their underlying causes in documents. It extends t…
An Efficient Transfer Learning Framework for Multiagent Reinforcement Learning
Tianpei Yang, Weixun Wang, Hongyao Tang +9
Transfer Learning has shown great potential to enhance single-agent Reinforcement Learning (RL) efficiency. Similarly, Multiagent RL (MARL) can also be accelerated if agents can sh…