Provable benefits of annealing for estimating normalizing constants: Importance Sampling, Noise-Contrastive Estimation, and beyond - NeurIPS 2023
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Updated
Oct 5, 2023 - Python
Provable benefits of annealing for estimating normalizing constants: Importance Sampling, Noise-Contrastive Estimation, and beyond - NeurIPS 2023
we propose a novel FusionGDA model, which utilises a pre-training phase with a fusion module to enrich the gene and disease semantic representations encoded by pre-trained language models.
Code for the Paper : NBC-Softmax : Darkweb Author fingerprinting and migration tracking (https://arxiv.org/abs/2212.08184)
Pre-training Multi-task Contrastive Learning Models for Scientific Literature Understanding (Findings of EMNLP'23)
Self-Supervised Contrastive Learning for Colon Pathology Classification
Contrastive Unlearning
This project has a comprehensive exploration of two key topics: Softmax Regression and Contrastive Representation Learning. The dataset used for this project is the CIFAR-10 dataset, which can be accessed by link given below
Neural inverted index for fast and effective information retrieval
Implementation of NAACL 2024 main conference paper: Named Entity Recognition Under Domain Shift via Metric Learning for Life Science
RRCGAN:A Radiometric Resolution Compression Method for Optical Remote Sensing Images Using Contrastive Learning
Contrastive-LSH Embedding and Tokenization Technique for Multivariate Time Series Classification
Implementation of modulated sigmoid pairwise contrastive loss for self-supervised learning on images
Tumor detection and classification from abdominal ultrasound images using CenterNet with Contrastive Learning.
Code for the paper "Category-Level Pose Retrieval with Contrastive Features Learnt with Occlusion Augmentation"
Contrastive representation learning with PyTorch
[IMAGE24] Contrastive learning for deep tone mapping operator
A PyTorch-based system for highly accurate drug-target interaction predictions utilizing multi-modal large language models to discern structural affinities in drug-target pairs.
Official implementation of the ACL Findings 2023 paper: Multimedia Generative Script Learning for Task Planning
Comparing performance of different InfoNCE type losses used in contrastive learning.
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