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Found 5 papers, 3 papers with code
Where is the Truth? The Risk of Getting Confounded in a Continual World
A dataset is confounded if it is most easily solved via a spurious correlation which fails to generalize to new data.
BOWLL: A Deceptively Simple Open World Lifelong Learner
The quest to improve scalar performance numbers on predetermined benchmarks seems to be deeply engraved in deep learning.
Self-Expanding Neural Networks
The results of training a neural network are heavily dependent on the architecture chosen; and even a modification of only its size, however small, typically involves restarting the training process.
Gaussian Process Based Message Filtering for Robust Multi-Agent Cooperation in the Presence of Adversarial Communication
In this paper, we consider the problem of providing robustness to adversarial communication in multi-agent systems.
Multi-Vehicle Mixed-Reality Reinforcement Learning for Autonomous Multi-Lane Driving
In this article, we present a safe and efficient framework that enables the learning of driving policies for autonomous vehicles operating in a shared workspace, where the absence of collisions cannot be guaranteed.
