Yin Jun Phua

14 papers B 2Journal 8Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Can We Test Consciousness Theories on AI? Ablations, Markers, and Robustness.
CoRR
Yin Jun Phua
2025 J jnl
Future-proofing class-incremental learning.
Mach. Vis. Appl.
Quentin Jodelet, Xin Liu, Yin Jun Phua, Tsuyoshi Murata
2025 J jnl
Memory augmented using diffusion model for class-incremental learning.
Image Vis. Comput.
Quentin Jodelet, Xin Liu, Yin Jun Phua, Tsuyoshi Murata
2024 J jnl
DEGNN: Dual Experts Graph Neural Network Handling Both Edge and Node Feature Noise.
CoRR
Tai Hasegawa, Sukwon Yun, Xin Liu, Yin Jun Phua, Tsuyoshi Murata
2024 — conf
DEGNN: Dual Experts Graph Neural Network Handling both Edge and Node Feature Noise.
PAKDD (2)
Tai Hasegawa, Sukwon Yun, Xin Liu, Yin Jun Phua, Tsuyoshi Murata
2024 J jnl
Future-Proofing Class Incremental Learning.
CoRR
Quentin Jodelet, Xin Liu, Yin Jun Phua, Tsuyoshi Murata
2024 — conf
Variable Assignment Invariant Neural Networks for Learning Logic Programs.
NeSy (1)
Yin Jun Phua, Katsumi Inoue
2024 J jnl
Variable Assignment Invariant Neural Networks for Learning Logic Programs.
CoRR
Yin Jun Phua, Katsumi Inoue
2023 — conf
Class-Incremental Learning using Diffusion Model for Distillation and Replay.
ICCV (Workshops)
Quentin Jodelet, Xin Liu, Yin Jun Phua, Tsuyoshi Murata
2023 J jnl
Class-Incremental Learning using Diffusion Model for Distillation and Replay.
CoRR
Quentin Jodelet, Xin Liu, Yin Jun Phua, Tsuyoshi Murata
2021 B conf
Learning Logic Programs Using Neural Networks by Exploiting Symbolic Invariance.
ILP
Yin Jun Phua, Katsumi Inoue
2019 B conf
Learning Logic Programs from Noisy State Transition Data.
ILP
Yin Jun Phua, Katsumi Inoue
2019 J jnl
Learning Representation of Relational Dynamics with Delays and Refining with Prior Knowledge.
FLAP
Yin Jun Phua, Tony Ribeiro, Katsumi Inoue
2017 — conf
Learning Logic Program Representation for Delayed Systems With Limited Training Data.
ILP (Late Breaking Papers)
Yin Jun Phua, Tony Ribeiro, Sophie Tourret, Katsumi Inoue