Topic: Dynamic Curriculum Learning for Imbalanced Data Classification Keywords: Curriculum Learning Class Imbalance Sampling Strategy Triplet Loss Reference: Wang, Y., Gan, W., Yang, J., …
2024.07.31.
변유정
Topic: Correlation Recurrent Units A Novel Neural Architecture for Improving the Predictive Performance of Time-Series Data Keywords: Neural network RNN STL Decomposition Reference: Sim, Su…
2024.07.30.
김찬호
Topic: Periodic activation function Keywords: Neural network Periodicity Activation function Extrapolation Reference: Liu et al., “Neural Networks Fail to Learn Periodic Functions and How …
2024.07.23
김주헌
Topic: What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? keywords: Semantic segmentation Depth regression Uncertainty estimation Aleatoric uncertainty epistemic unc…
이형권
Introduction to Bayesian Neural Networks
이종석
Topic: Kolmogorov-Arnold Networks Keywords: Kolmogorov–Arnold representation theorem MLP Deep learning Interpretability Continual Learning
2024.07.10
김철규
Topic: Recommender System Keywords: GNN GC-MC Message passing Matrix Factorization Reference: Berg, Rianne van den, Thomas N. Kipf, and Max Welling. "Graph convolutional matrix completion.…
2024.06.04.
Topic: Missing imputation Keywords: Missing mechanism Missing data handling MICE (multiple imputation by chained equations) Reference: Azur et al., "Multiple imputation by chained equations…
2024.05.14
Topic: ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation keywords: Semantic segmentation Uncertainty estimation Predictive uncertainty Aleatoric …
2024.04.16
Topic: Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels Keywords: Bayesian Optimization Few-Shot Deep Kernels Meta-Learning
2024.04.02
Topic : Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Keywords: Gradient-weighted class activation map Visual Explanations Localization Map Reference: 1. …
2024.03.19.
Topic : Federated Bayesian Optimization via Thompson Sampling Keywords: Federated Learning Bayesian Optimization Random Fourier Features Thompson Sampling Federated Bayesian Optimization Hyp…
2024.04.02.
구본영
Topic : Linear Coefficient Estimation under Interaction Effect Keywords: Generalized Additive Models Distributional Regression Semi-Structured Effects Mixture Density Networks Reference: 1…
2024.03.26.
부도현
Topic : Debiased Causal Tree: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding Keywords: Causal Inference Heterogeneous Treatment Effects Estimation Causal Tree Confoundi…
2024.02.29.
Topic : Tabular Data and Neural Nerworks Keywords: Deep tabular learning, Numerical Feature embedding, Reference: 1. Grinsztajn, Léo, Edouard Oyallon, and Gaël Varoquaux. "Why do tree-b…
2024-02-29
김현호