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Found 8 papers, 0 papers with code
Neural Motion Planning for Autonomous Parking
This paper presents a hybrid motion planning strategy that combines a deep generative network with a conventional motion planning method.
Multi-Head Attention based Probabilistic Vehicle Trajectory Prediction
This paper presents online-capable deep learning model for probabilistic vehicle trajectory prediction.
Coupled Representation Learning for Domains, Intents and Slots in Spoken Language Understanding
Our proposed model learns the vector representation of intents based on the slots tied to these intents by aggregating the representations of the slots.
Efficient Large-Scale Neural Domain Classification with Personalized Attention
In this paper, we explore the task of mapping spoken language utterances to one of thousands of natural language understanding domains in intelligent personal digital assistants (IPDAs).
Efficient Large-Scale Domain Classification with Personalized Attention
In this paper, we explore the task of mapping spoken language utterances to one of thousands of natural language understanding domains in intelligent personal digital assistants (IPDAs).
A Scalable Neural Shortlisting-Reranking Approach for Large-Scale Domain Classification in Natural Language Understanding
Intelligent personal digital assistants (IPDAs), a popular real-life application with spoken language understanding capabilities, can cover potentially thousands of overlapping domains for natural language understanding, and the task of finding the best domain to handle an utterance becomes a challenging problem on a large scale.
Domain Attention with an Ensemble of Experts
When given domain K + 1, our model uses a weighted combination of the K domain experts{'} feedback along with its own opinion to make predictions on the new domain.
Adversarial Adaptation of Synthetic or Stale Data
Both cause a distribution mismatch between training and evaluation, leading to a model that overfits the flawed training data and performs poorly on the test data.
