Kay Chen Tan
12 papers · 2020–2026 · 3 venues · across top CS/AI venues
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transfer learning
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spiking neural network
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partial differential equation
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energy efficiency
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genetic programming
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symbolic regression
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large language model
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multi-objective optimization
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neuromorphic computing
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automatic differentiation
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geometric deep learning
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neural architecture search
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loss function optimization
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temporal modeling
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representation learning
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multi-label learning
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Papers
Distributional Priors Guided Diffusion for Generating 3D Molecules in Low Data Regimes
AAAI 2026
Fading the Digital Ink: A Universal Black-Box Attack Framework for 3DGS Watermarking Systems
AAAI 2026
Design Principle Transfer in Neural Architecture Search via Large Language Models
AAAI 2025
Interpretable Solutions for Multi-Physics PDEs Using T-NNGP
AAAI 2025
Neuromorphic Sequential Arena: A Benchmark for Neuromorphic Temporal Processing
IJCAI 2025
An Interpretable Approach to the Solutions of High-Dimensional Partial Differential Equations
AAAI 2024
Generating Diagnostic and Actionable Explanations for Fair Graph Neural Networks
AAAI 2024
Large Language Model-Enhanced Algorithm Selection: Towards Comprehensive Algorithm Representation
IJCAI 2024
TC-LIF: A Two-Compartment Spiking Neuron Model for Long-Term Sequential Modelling
AAAI 2024
Robust Graph Meta-Learning via Manifold Calibration with Proxy Subgraphs
AAAI 2023
Crowd Counting in the Frequency Domain
CVPR 2022
Multi-label Feature Selection via Global Relevance and Redundancy Optimization
IJCAI 2020