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Tianjin Huang
Tianjin Huang
Asst. Professor, CS@University of Exeter & Researcher Fellow, CS@TU/e
Verified email at tue.nl - Homepage
Title
Cited by
Cited by
Year
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
812021
Hop-count based self-supervised anomaly detection on attributed networks
T Huang, Y Pei, V Menkovski, M Pechenizkiy
ECML 2022, 2021
312021
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
282023
Visual prompting upgrades neural network sparsification: A data-model perspective
C Jin, T Huang, Y Zhang, M Pechenizkiy, S Liu, S Liu, T Chen
AAAI 2025, 2023
262023
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
222024
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
212022
Bridging the Performance Gap between FGSM and PGD Adversarial Training
T Huang, V Menkovski, Y Pei, M Pechenizkiy
arXiv preprint arXiv:2011.05157, 2020
202020
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
192022
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
172024
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
122022
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
112023
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
82022
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
62021
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
52017
Composable Interventions for Language Models
A Kolbeinsson, K O'Brien, T Huang, S Gao, S Liu, JR Schwarz, A Vaidya, ...
arXiv preprint arXiv:2407.06483, 2024
32024
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
32023
Calibrated adversarial training
T Huang, V Menkovski, Y Pei, M Pechenizkiy
Asian Conference on Machine Learning, 626-641, 2021
32021
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained Graph Tickets
T Huang, T Chen, M Fang, V Menkovski, J Zhao, L Yin, Y Pei, DC Mocanu, ...
Learning on Graphs Conference (Oral & Best Paper Award), 0
1*
Are Sparse Neural Networks Better Hard Sample Learners?
Q Xiao, B Wu, L Yin, CN Gadzinski, T Huang, M Pechenizkiy, DC Mocanu
BMVC2024, 2024
2024
(PASS) Visual Prompt Locates Good Structure Sparsity through a Recurrent HyperNetwork
T Huang, F Meng, L Shen, F Liu, Y Pei, M Pechenizkiy, S Liu, T Chen
arXiv preprint arXiv:2407.17412, 2024
2024
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