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Found 12 papers, 5 papers with code
Accelerating Multi-Agent Planning Using Graph Transformers with Bounded Suboptimality
Though it is complete and optimal, it does not scale well.
See What the Robot Can't See: Learning Cooperative Perception for Visual Navigation
We consider the problem of navigating a mobile robot towards a target in an unknown environment that is endowed with visual sensors, where neither the robot nor the sensors have access to global positioning information and only use first-person-view images.
A Framework for Real-World Multi-Robot Systems Running Decentralized GNN-Based Policies
We demonstrate our framework on a case-study that requires tight coordination between robots, and present first-of-a-kind results that show successful real-world deployment of GNN-based policies on a decentralized multi-robot system relying on Adhoc communication.
Graph Neural Network Guided Local Search for the Traveling Salesperson Problem
To close this gap, we present a hybrid data-driven approach for solving the TSP based on Graph Neural Networks (GNNs) and Guided Local Search (GLS).
The Holy Grail of Multi-Robot Planning: Learning to Generate Online-Scalable Solutions from Offline-Optimal Experts
Many multi-robot planning problems are burdened by the curse of dimensionality, which compounds the difficulty of applying solutions to large-scale problem instances.
Graph Neural Networks for Decentralized Multi-Robot Submodular Action Selection
We demonstrate the performance of our GNN-based learning approach in a scenario of active target tracking with large networks of robots.
Synthesizing Decentralized Controllers with Graph Neural Networks and Imitation Learning
Dynamical systems consisting of a set of autonomous agents face the challenge of having to accomplish a global task, relying only on local information.
Message-Aware Graph Attention Networks for Large-Scale Multi-Robot Path Planning
Our Message-Aware Graph Attention neTwork (MAGAT) is based on a key-query-like mechanism that determines the relative importance of features in the messages received from various neighboring robots.
Real-time Surgical Environment Enhancement for Robot-Assisted Minimally Invasive Surgery Based on Super-Resolution
In Robot-Assisted Minimally Invasive Surgery (RAMIS), a camera assistant is normally required to control the position and zooming ratio of the laparoscope, following the surgeon's instructions.
Looking At The Body: Automatic Analysis of Body Gestures and Self-Adaptors in Psychological Distress
Compared to modalities such as face, head, and vocal, research investigating the use of the body modality for these tasks is relatively sparse.
Ranked #1 on
Anxiety Detection
on Well-being Dataset
Text Classification with Lexicon from PreAttention Mechanism
What's more, there is no an effective way to use a lexicon in a neural network.
Hierarchical Transformer Network for Utterance-level Emotion Recognition
To address these problems, we propose a hierarchical transformer framework (apart from the description of other studies, the "transformer" in this paper usually refers to the encoder part of the transformer) with a lower-level transformer to model the word-level input and an upper-level transformer to capture the context of utterance-level embeddings.
Ranked #1 on
Emotion Recognition in Conversation
on EmotionPush
