Linkage-based multi-object clustering/grouping using GCN
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Updated
Aug 23, 2022 - Jupyter Notebook
Linkage-based multi-object clustering/grouping using GCN
PyTorch implementation of graph convolutional networks (GCNs).
Implementation of various collaborative filtering methods for recommender systems with implicit feedback
Code for my Master's thesis "Exploiting Spatial-Temporal Relationships for Occlusion-Robust 3D Human Pose Estimation" at TUM
Survival Prediction for Gastric Cancer via Multimodal Learning of Whole Slide Images and Gene Expression -- BIBM 2022
Graph Convolutional Branch and Bound solver for the Traveling Salesman Problem.
A novel method for link prediction in temporal networks based on EvolveGCN (Aldo Pareja et al) and GAT (Petar Velickovic et al)
Learning to Solve Multiresolution Matrix Factorization by Manifold Optimization and Evolutionary Metaheuristics
Modeling the external convergence from photometric catalogs
Predicting probable drug-binding sites for thousands of human proteins using AlphaFold2 predicted 3D protein structures.
Small Molecular Graph Generation for Drug Discovery
Fraud detection using Graph Convolutional Networks
A Jupyter notebook for a project centered around 'Group Recommendation Systems (GRS)' utilizing the 'GcPp' clustering approach.
The implementation of paper "HPOFiller: identifying missing protein-phenotype associations by graph convolutional network".
STAD-GCN: Spatial-Temporal Attention-based Dynamic Graph Convolutional Network for Retail Market Price Prediction, pytorch version (ESWA 2024)
The official project website of "3D Human Pose Lifting with Grid Convolution" (GridConv for short, oral in AAAI 2023)
NLP - Semantic Role Labeling using GCN, Bert and Biaffine Attention Layer. Developed in Pytorch
The implementation, training and evaluation of a Structure Seer machine learning model designed for reconstruction of adjacency of a molecular graph from the labelling of its nodes.
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