Mia Liu

According to our database1, Mia Liu authored at least 20 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Corrigendum: Applications and techniques for fast machine learning in science.
Frontiers Big Data, 2024

Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics.
CoRR, 2024

2023
Interpretable Geometric Deep Learning via Learnable Randomness Injection.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Editorial: Efficient AI in particle physics and astrophysics.
Frontiers Artif. Intell., 2022

Applications and Techniques for Fast Machine Learning in Science.
Frontiers Big Data, 2022

Interpretable Geometric Deep Learning via Learnable Randomness Injection.
CoRR, 2022

Data Science and Machine Learning in Education.
CoRR, 2022

Physics Community Needs, Tools, and Resources for Machine Learning.
CoRR, 2022

Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism.
Proceedings of the International Conference on Machine Learning, 2022

2021
Compressing deep neural networks on FPGAs to binary and ternary precision with hls4ml.
Mach. Learn. Sci. Technol., 2021

GPU coprocessors as a service for deep learning inference in high energy physics.
Mach. Learn. Sci. Technol., 2021

Fast convolutional neural networks on FPGAs with hls4ml.
Mach. Learn. Sci. Technol., 2021

Applications and Techniques for Fast Machine Learning in Science.
CoRR, 2021

hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices.
CoRR, 2021

Fast convolutional neural networks on FPGAs with hls4ml.
CoRR, 2021

2020
Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics.
Frontiers Big Data, 2020

Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs.
CoRR, 2020

GPU coprocessors as a service for deep learning inference in high energy physics.
CoRR, 2020

FPGAs-as-a-Service Toolkit (FaaST).
Proceedings of the 2020 IEEE/ACM International Workshop on Heterogeneous High-performance Reconfigurable Computing, 2020

2019
FPGA-Accelerated Machine Learning Inference as a Service for Particle Physics Computing.
Comput. Softw. Big Sci., December, 2019


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