PyTorch implementation of TransFASNet: a single-branch Transformer with contrastive self-supervised pretraining (NT-Xent) for credit card fraud detection on tabular data.
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Updated
Sep 7, 2026 - Python
PyTorch implementation of TransFASNet: a single-branch Transformer with contrastive self-supervised pretraining (NT-Xent) for credit card fraud detection on tabular data.
Educational implementation of V-JEPA (Video Joint Embedding Predictive Architecture) in PyTorch. Includes Conv3D tubelet embeddings, Video ViT, EMA target encoder, spatiotemporal masking, linear probing, retrieval evaluation, and effective-rank analysis on Something-Something V2.
End-to-end Self-Supervised Visual Feature Clustering project. Extracts deep representations using frozen ResNet50 transfer features from CIFAR-10 data, benchmarking K-Means, DBSCAN, and GMM. Features an interactive UMAP web dashboard and real-time visual query search engine.
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