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2020 – today
- 2025
[j2]Quentin Jodelet, Xin Liu, Yin Jun Phua, Tsuyoshi Murata:
Future-proofing class-incremental learning. Mach. Vis. Appl. 36(1): 16 (2025)- 2024
- [c6]Yin Jun Phua
, Katsumi Inoue:
Variable Assignment Invariant Neural Networks for Learning Logic Programs. NeSy (1) 2024: 47-61 - [c5]Tai Hasegawa, Sukwon Yun, Xin Liu, Yin Jun Phua, Tsuyoshi Murata:
DEGNN: Dual Experts Graph Neural Network Handling both Edge and Node Feature Noise. PAKDD (2) 2024: 376-389 - [i4]Quentin Jodelet, Xin Liu, Yin Jun Phua, Tsuyoshi Murata:
Future-Proofing Class Incremental Learning. CoRR abs/2404.03200 (2024) - [i3]Tai Hasegawa, Sukwon Yun, Xin Liu, Yin Jun Phua, Tsuyoshi Murata:
DEGNN: Dual Experts Graph Neural Network Handling Both Edge and Node Feature Noise. CoRR abs/2404.09207 (2024) - [i2]Yin Jun Phua, Katsumi Inoue:
Variable Assignment Invariant Neural Networks for Learning Logic Programs. CoRR abs/2408.10709 (2024) - 2023
- [c4]Quentin Jodelet, Xin Liu, Yin Jun Phua, Tsuyoshi Murata:
Class-Incremental Learning using Diffusion Model for Distillation and Replay. ICCV (Workshops) 2023: 3417-3425 - [i1]Quentin Jodelet, Xin Liu, Yin Jun Phua, Tsuyoshi Murata:
Class-Incremental Learning using Diffusion Model for Distillation and Replay. CoRR abs/2306.17560 (2023) - 2021
- [c3]Yin Jun Phua, Katsumi Inoue:
Learning Logic Programs Using Neural Networks by Exploiting Symbolic Invariance. ILP 2021: 203-218
2010 – 2019
- 2019
- [j1]Yin Jun Phua, Tony Ribeiro, Katsumi Inoue:
Learning Representation of Relational Dynamics with Delays and Refining with Prior Knowledge. FLAP 6(4): 695-708 (2019) - [c2]Yin Jun Phua, Katsumi Inoue:
Learning Logic Programs from Noisy State Transition Data. ILP 2019: 72-80 - 2017
- [c1]Yin Jun Phua, Tony Ribeiro, Sophie Tourret, Katsumi Inoue:
Learning Logic Program Representation for Delayed Systems With Limited Training Data. ILP (Late Breaking Papers) 2017: 27-37
Coauthor Index
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