activity
20162022
most citedAutomatic feature learning for vulnerability prediction

88 citations · 260 across the 29 of their papers we have counts for

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Showing cs.AIShow all

6 papers · 1 filter

cs.AI20221 cited

Learning to Discover Medicines

Tri Minh Nguyen, Thin Nguyen, Truyen Tran

Discovering new medicines is the hallmark of human endeavor to live a better and longer life. Yet the pace of discovery has slowed down as we need to venture into more wildly unexp…

cs.AI2021

Counterfactual Explanation with Multi-Agent Reinforcement Learning for Drug Target Prediction

Tri Minh Nguyen, Thomas P Quinn, Thin Nguyen +1

Motivation: Many high-performance DTA models have been proposed, but they are mostly black-box and thus lack human interpretability. Explainable AI (XAI) can make DTA models more t…

cs.AI20201 cited

Theory of Mind with Guilt Aversion Facilitates Cooperative Reinforcement Learning

Dung Nguyen, Svetha Venkatesh, Phuoc Nguyen +1

Guilt aversion induces experience of a utility loss in people if they believe they have disappointed others, and this promotes cooperative behaviour in human. In psychological game…

cs.AI2019

Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning

Thommen George Karimpanal, Santu Rana, Sunil Gupta +2

Prior access to domain knowledge could significantly improve the performance of a reinforcement learning agent. In particular, it could help agents avoid potentially catastrophic e…

cs.AI2018

Relational dynamic memory networks

Trang Pham, Truyen Tran, Svetha Venkatesh

Neural networks excel in detecting regular patterns but are less successful in representing and manipulating complex data structures, possibly due to the lack of an external memory…

cs.AI20184 cited

Knowledge Graph Embedding with Multiple Relation Projections

Kien Do, Truyen Tran, Svetha Venkatesh

Knowledge graphs contain rich relational structures of the world, and thus complement data-driven machine learning in heterogeneous data. One of the most effective methods in repre…