Eksplorasi makalah akademik, arsitektur sistem, dan implementasi kode.
# Beyond Fixed Embeddings: Mastering Inductive Learning with GraphSAGE In the early days of Graph Neural Networks (GNNs), we were largely limited to...
# Bridging the Gap: TabNet and the Fusion of Decision Trees with Deep Learning For years, the machine learning community has faced a persistent dicho...
# Beyond the MLP: Revisiting Deep Learning for Tabular Data For years, the consensus in the data science community has been clear: **if your data is...
# Breaking the Limits of GNNs: Understanding the Graph Isomorphism Network (GIN) In the rapidly evolving landscape of Geometric Deep Learning, a fund...
# Mastering node2vec: Bridging Graph Topology and Vector Embeddings In the era of Big Data, graphs are everywhereāfrom social networks and protein-pr...
# Beyond Gradient Descent: TabPFN and the Rise of In-Context Learning for Tabular Data For decades, the gold standard for tabular data has been a tug...
# Mastering Heterogeneous Graphs: A Deep Dive into Heterogeneous Graph Attention Networks (HAN) In the real world, data is rarely homogeneous. Consid...
# Mastering Graph Neural Networks: Inside the PyTorch Geometric "Gather-Scatter" Paradigm Graph-structured data is everywhereāfrom the social network...
# Mastering Temporal Graph Networks (TGNs): Learning from Continuous-Time Dynamic Graphs In the real world, graphs are rarely static. Whether it's a...
# Beyond Fixed Graphs: Discovering Hidden Structures with Graph Transformer Networks (GTN) In the world of Graph Neural Networks (GNNs), we usually t...