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Found 7 papers, 2 papers with code
LSP Framework: A Compensatory Model for Defeating Trigger Reverse Engineering via Label Smoothing Poisoning
Based on this paradigm, we propose a new perspective to defeat trigger reverse engineering by manipulating the classification confidence of backdoor samples.
AED-PADA:Improving Generalizability of Adversarial Example Detection via Principal Adversarial Domain Adaptation
Specifically, our approach identifies the Principal Adversarial Domains (PADs), i. e., a combination of features of the adversarial examples from different attacks, which possesses large coverage of the entire adversarial feature space.
Computational Discovery of Microstructured Composites with Optimal Stiffness-Toughness Trade-Offs
The conflict between stiffness and toughness is a fundamental problem in engineering materials design.
Data-Efficient Graph Grammar Learning for Molecular Generation
This is a non-trivial task for neural network-based generative models since the relevant chemical knowledge can only be extracted and generalized from the limited training data.
Designing Composites with Target Effective Young's Modulus using Reinforcement Learning
Advancements in additive manufacturing have enabled design and fabrication of materials and structures not previously realizable.
AutoOED: Automated Optimal Experimental Design Platform with Data- and Time-Efficient Multi-Objective Optimization
We present AutoOED, an Automated Optimal Experimental Design platform powered by machine learning to accelerate discovering solutions with optimal objective trade-offs.
Learning to Reason in Round-based Games: Multi-task Sequence Generation for Purchasing Decision Making in First-person Shooters
In this work, we propose a Sequence Reasoner with Round Attribute Encoder and Multi-Task Decoder to interpret the strategies behind the round-based purchasing decisions.
