Search Results for author: Yash Raj Shrestha

Found 10 papers, 4 papers with code

NCDD: Nearest Centroid Distance Deficit for Out-Of-Distribution Detection in Gastrointestinal Vision

1 code implementation2 Dec 2024 Sandesh Pokhrel, Sanjay Bhandari, Sharib Ali, Tryphon Lambrou, Anh Nguyen, Yash Raj Shrestha, Angus Watson, Danail Stoyanov, Prashnna Gyawali, Binod Bhattarai

Evaluations across multiple deep learning architectures and two publicly available benchmarks, Kvasir2 and Gastrovision, demonstrate the effectiveness of our approach compared to several state-of-the-art methods.

Out-of-Distribution Detection Out of Distribution (OOD) Detection

Difficulty Estimation and Simplification of French Text Using LLMs

no code implementations25 Jul 2024 Henri Jamet, Yash Raj Shrestha, Michalis Vlachos

We leverage generative large language models for language learning applications, focusing on estimating the difficulty of foreign language texts and simplifying them to lower difficulty levels.

Transfer Learning

Cross-Task Data Augmentation by Pseudo-label Generation for Region Based Coronary Artery Instance Segmentation

no code implementations8 Oct 2023 Sandesh Pokhrel, Sanjay Bhandari, Eduard Vazquez, Yash Raj Shrestha, Binod Bhattarai

In this study, we introduce the use of pseudo-labels to address the issue of limited data in the angiographic dataset to enhance the performance of the baseline YOLO model.

Coronary Artery Segmentation Data Augmentation +4

Large Language Models for Difficulty Estimation of Foreign Language Content with Application to Language Learning

no code implementations10 Sep 2023 Michalis Vlachos, Mircea Lungu, Yash Raj Shrestha, Johannes-Rudolf David

This is accomplished by identifying content on topics that the user is interested in, and that closely align with the learner's proficiency level in that foreign language.

Towards Automatic Bias Detection in Knowledge Graphs

1 code implementation Findings (EMNLP) 2021 Daphna Keidar, Mian Zhong, Ce Zhang, Yash Raj Shrestha, Bibek Paudel

With the recent surge in social applications relying on knowledge graphs, the need for techniques to ensure fairness in KG based methods is becoming increasingly evident.

Bias Detection Fairness +2

Augmenting Organizational Decision-Making with Deep Learning Algorithms: Principles, Promises, and Challenges

no code implementations2 Nov 2020 Yash Raj Shrestha, Vaibhav Krishna, Georg von Krogh

The current expansion of theory and research on artificial intelligence in management and organization studies has revitalized the theory and research on decision-making in organizations.

Decision Making Management

Adversarial Learning for Debiasing Knowledge Graph Embeddings

no code implementations29 Jun 2020 Mario Arduini, Lorenzo Noci, Federico Pirovano, Ce Zhang, Yash Raj Shrestha, Bibek Paudel

As a second step, we explore gender bias in KGE, and a careful examination of popular KGE algorithms suggest that sensitive attribute like the gender of a person can be predicted from the embedding.

Attribute Knowledge Graph Embeddings +2

A Deep Learning Pipeline for Patient Diagnosis Prediction Using Electronic Health Records

no code implementations23 Jun 2020 Leopold Franz, Yash Raj Shrestha, Bibek Paudel

Second, machine learning algorithms that predict multiple disease diagnosis categories simultaneously remain underdeveloped.

BIG-bench Machine Learning Decision Making

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