Humans and animals explore their environment and acquire useful skills e...
Geometric methods for solving open-world off-road navigation tasks, by
l...
Reinforcement learning (RL) provides a framework for learning goal-direc...
Humans have a remarkable ability to make decisions by accurately reasoni...
We describe a robotic learning system for autonomous navigation in diver...
We propose a learning-based navigation system for reaching visually indi...
Reinforcement learning provides a general framework for flexible decisio...
Safe exploration presents a major challenge in reinforcement learning (R...
Out-of-training-distribution (OOD) scenarios are a common challenge of
l...
Predicting the future is a crucial first step to effective control, sinc...
Predicting the future is a crucial first step to effective control, sinc...
For autonomous vehicles (AVs) to behave appropriately on roads populated...
Automatically reasoning about future human behaviors is a difficult prob...
Imitation learning provides an appealing framework for autonomous contro...
The use of imitation learning to learn a single policy for a complex tas...
Humans are able to understand and perform complex tasks by strategically...
We address the problem of spatial segmentation of a 2D object in the con...
Recurrent neural networks (RNNs) are a vital modeling technique that rel...
While bigger and deeper neural network architectures continue to advance...
We address the problem of incrementally modeling and forecasting long-te...
We consider detecting objects in an image by iteratively selecting from ...