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Deceptrax123/README.md

Hi there, I am Nitish, welcome!

  • A deep learning enthusiast pursuing research in computer vision, NLP etc, Backend developer
  • Passionate in the fields of mathematics, statistics and quantum physics
  • Love watching movies,reading and connecting
  • Full time music addict, ranging from Kpop to Piano and Violin classics 🤝

Profile Summary

My Tech Stack

My Socials,Blog and Research

My Github Stats

repo commit
profile commits

Projects

Have a Great Day!

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  1. Detecting-Side-Effects-of-Adverse-Drug-Reactions-through-Drug-Drug-Interactions-using-Graph-Neural-N Detecting-Side-Effects-of-Adverse-Drug-Reactions-through-Drug-Drug-Interactions-using-Graph-Neural-N Public

    Official code of our paper titled "Detecting Side Effects of Addverse Drug Reactions through Drug-Drug Interactions using Graph Neural Networks and Self-Supervised Learning"

    Python 1

  2. Molecule-Chemical-Property-Prediction-using-Graph-Isomorphism-and-Adversarial-Pretraining Molecule-Chemical-Property-Prediction-using-Graph-Isomorphism-and-Adversarial-Pretraining Public

    Predict the properties of molecules through adversarial pre-training and Graph Isomorphism

    Python

  3. Defending-Graph-Neural-Networks-against-Adversarial-Attacks Defending-Graph-Neural-Networks-against-Adversarial-Attacks Public

    A self-supervised approach to train Graph Neural Networks to defend itself against Adversarial Attacks through Contrastive Learning and Negative Sampling

    Python 1

  4. Self-Supervised-Learning-using-YOLOv5-Backbone Self-Supervised-Learning-using-YOLOv5-Backbone Public

    Localize and segment multiple objects by pre-training the backbone of YOLOv5 using an autoencoder

    Python

  5. Spurious-Correlation-Mitigation-in-YOLOv5 Spurious-Correlation-Mitigation-in-YOLOv5 Public

    Autoencoder based approach for the mitigation of spurious correlations on YOLOv5 detections

  6. Differential-Equations-Using-Neural-Networks Differential-Equations-Using-Neural-Networks Public

    Solving ODEs with initial values and PDEs with Dirichlet and Mixed Boundary Conditions using neural networks

    Python 1