Tianjin Huang
Tianjin Huang
Incoming Asst. Professor, CS@University of Exeter; Lecturer, CS@Unviersity of Aberdeen
Verified email at - Homepage
Cited by
Cited by
ResGCN: attention-based deep residual modeling for anomaly detection on attributed networks
Y Pei, T Huang, W van Ipenburg, M Pechenizkiy
[DSAA] 2021 IEEE 8th International Conference on Data Science and Advanced …, 2021
Hop-count based self-supervised anomaly detection on attributed networks
T Huang, Y Pei, V Menkovski, M Pechenizkiy
ECML 2022, 2021
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!
S Liu, T Chen, Z Zhang, X Chen, T Huang, A Jaiswal, Z Wang
ICLR 2023, 2023
Direction-aggregated attack for transferable adversarial examples
T Huang, V Menkovski, Y Pei, Y Wang, M Pechenizkiy
ACM Journal on Emerging Technologies in Computing Systems (JETC) 18 (3), 1-22, 2022
Bridging the Performance Gap between FGSM and PGD Adversarial Training
T Huang, V Menkovski, Y Pei, M Pechenizkiy
arXiv preprint arXiv:2011.05157, 2020
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets
T Huang, T Chen, M Fang, V Menkovski, J Zhao, L Yin, Y Pei, DC Mocanu, ...
LoG 2022 (Oral & Best Paper Award), 2022
Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost
L Yin, S Liu, F Meng, T Huang, V Menkovski, M Pechenizkiy
AAAI 2023, 2022
Are Large Kernels Better Teachers than Transformers for ConvNets?
T Huang, L Yin, Z Zhang, L Shen, M Fang, M Pechenizkiy, Z Wang, S Liu
ICML 2023, 2023
Superposing Many Tickets into One: A Performance Booster for Sparse Neural Network Training
L Yin, V Menkovski, M Fang, T Huang, Y Pei, M Pechenizkiy, DC Mocanu, ...
UAI 2022, 2022
RT-GCN: Gaussian-based spatiotemporal graph convolutional network for robust traffic prediction
Y Liu, S Rasouli, M Wong, T Feng, T Huang*
Information Fusion 102, 102078, 2024
Dynamic sparsity is channel-level sparsity learner
L Yin, G Li, M Fang, L Shen, T Huang, Z Wang, V Menkovski, X Ma, ...
Advances in Neural Information Processing Systems 36, 2024
On generalization of graph autoencoders with adversarial training
T Huang, Y Pei, V Menkovski, M Pechenizkiy
[ECML2021] Machine Learning and Knowledge Discovery in Databases. Research …, 2021
A new method to estimate changes in glacier surface elevation based on polynomial fitting of sparse ICESat—GLAS footprints
T Huang, L Jia, M Menenti, J Lu, J Zhou, G Hu
Sensors 17 (8), 1803, 2017
Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective
C Jin, T Huang, Y Zhang, M Pechenizkiy, S Liu, S Liu, T Chen
arXiv preprint arXiv:2312.01397, 2023
Calibrated adversarial training
T Huang, V Menkovski, Y Pei, M Pechenizkiy
Asian Conference on Machine Learning, 626-641, 2021
Enhancing Adversarial Training via Reweighting Optimization Trajectory
T Huang, S Liu, T Chen, M Fang, L Shen, V Menkovski, L Yin, Y Pei, ...
ECML 2023, 2023
The Counterattack of CNNs in Self-Supervised Learning: Larger Kernel Size might be All You Need
T Huang, T Chen, Z Wang, S Liu
arXiv preprint arXiv:2312.05695, 2023
Heterophily-Based Graph Neural Network for Imbalanced Classification
Z Liang, Y Li, T Huang, A Saxena, Y Pei, M Pechenizkiy
International Conference on Complex Networks and Their Applications, 74-86, 2023
() Visual Prompt Locates Good Structure Sparisty through a Recurent HyperNetwork
T Huang, M Fang, L Shen, F Liu, Y Pei, M Pechenizkiy, S Liu, T Chen
The Power of Minimalism in Long Sequence Time-series Forecasting
Z Sun, M Fang, D Song, D Li, T Huang, Q Peng
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