Comparing performance of different InfoNCE type losses used in contrastive learning.
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Updated
Jun 12, 2024 - Python
Comparing performance of different InfoNCE type losses used in contrastive learning.
Self-Supervised Noise Embeddings (Self-SNE)
Simple Contrastive Embedding of the Primary sequence of T cell Receptors
TC (MICCAI 2024) official code
Train Models Contrastively in Pytorch
A python library for self-supervised learning on images.
ProTrek: Navigating the Protein Universe through Tri-Modal Contrastive Learning
[WSDM'2024 Oral] "SSLRec: A Self-Supervised Learning Framework for Recommendation"
An official PyTorch implementation of the CRIS paper
Official Implementation for the paper Deep Domain Adaptation: A Sim2Real Neural Approach for Improving Eye-Tracking System.
Neural inverted index for fast and effective information retrieval
LibAUC: A Deep Learning Library for X-Risk Optimization
[WACV 2024 Oral] - ARNIQA: Learning Distortion Manifold for Image Quality Assessment
[BMVC 2022] This is the official code of our Paper "Revisiting Self-Supervised Contrastive Learning for Facial Expression Recognition"
Video Foundation Models & Data for Multimodal Understanding
[NeurIPS 2023] This repository includes the official implementation of our paper "An Inverse Scaling Law for CLIP Training"
[ICML 2023] Official implementation of "A randomized schur complement based graph augmentor"
Medical Diagnosis using Contrastive Learning
CellContrast: Reconstructing Spatial Relationships in Single-Cell RNA Sequencing Data via Deep Contrastive Learning
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