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03/14/2023
Adaptive Policy Learning for Offline-to-Online Reinforcement Learning
Conventional reinforcement learning (RL) needs an environment to collect...
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02/03/2023
DAMS-LIO: A Degeneration-Aware and Modular Sensor-Fusion LiDAR-inertial Odometry
The fusion scheme is crucial to the multi-sensor fusion method that is t...
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11/23/2022
Benchmarking variational quantum circuits with permutation symmetry
We propose SnCQA, a set of hardware-efficient variational circuits of eq...
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11/14/2022
Group-Equivariant Neural Networks with Fusion Diagrams
Many learning tasks in physics and chemistry involve global spatial symm...
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11/10/2022
Quantum Power Flows: From Theory to Practice
Climate change is becoming one of the greatest challenges to the sustain...
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07/15/2022
On the Super-exponential Quantum Speedup of Equivariant Quantum Machine Learning Algorithms with SU(d) Symmetry
We introduce a framework of the equivariant convolutional algorithms whi...
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12/14/2021
Speeding up Learning Quantum States through Group Equivariant Convolutional Quantum Ansätze
We develop a theoretical framework for S_n-equivariant quantum convoluti...
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06/02/2021
An Extendible, Graph-Neural-Network-Based Approach for Accurate Force Field Development of Large Flexible Organic Molecules
An accurate force field is the key to the success of all molecular mecha...
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11/02/2020
Cooperative Heterogeneous Deep Reinforcement Learning
Numerous deep reinforcement learning agents have been proposed, and each...
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03/06/2017
An optimal hierarchical clustering approach to segmentation of mobile LiDAR point clouds
This paper proposes a hierarchical clustering approach for the segmentat...
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10/15/2016
