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
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)
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
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
Implementation of modulated sigmoid pairwise contrastive loss for self-supervised learning on images
Code for the paper "Category-Level Pose Retrieval with Contrastive Features Learnt with Occlusion Augmentation"
[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.
Contrastive representation learning with PyTorch
Employ contrastive learning to enhance the ResNet-50 performace for skin lesion classification.
"DACL: Learning a Domain-Agnostic Contrastive Representation for Dense Prediction beyond Distribution Gap" (arXiv)
SimCLR implementation in PyTorch.
PyTorch implementation of SimSiam paper
This project is concerned with my participating in the RuNNE competition https://github.com/dialogue-evaluation/RuNNE
Official source code for AAAI 2023 paper: Uniform Sequence Better: Time Interval Aware Data Augmentation for Sequential Recommendation. AAAI, 2023.
The code for the paper "GMMFormer: Gaussian-Mixture-Model Based Transformer for Efficient Partially Relevant Video Retrieval" (AAAI'24)
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