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deyh2020's Projects

rliable icon rliable

[NeurIPS'21 Outstanding Paper] Library for reliable evaluation on RL and ML benchmarks, even with only a handful of seeds.

ro_puf icon ro_puf

Ring Oscillator Physically Unclonable Funtion

roadmaps icon roadmaps

This repo is to add pages on various career paths and roadmaps such as data scientist, software engineer etc.

robustness-cs icon robustness-cs

Measuring the robustness of compressive sensing methods (including deep-learning-based ones) for image reconstruction.

rram-radar-tuning icon rram-radar-tuning

Code and repository for RRAM RADAR programming method: https://doi.org/10.1109/TED.2021.3097975

sca-dpa icon sca-dpa

Side channel attack (SCA) of AES with Differential Power Analysis (DPA)

sca-neuroevolution icon sca-neuroevolution

Neuroevolution to optimise the weights of a neural network for power side-channel attacks.

scatternet icon scatternet

Code for all work presented in Nanophotonic Particle Simulation and Inverse Design Using Artificial Neural Networks

schrodinger-pde icon schrodinger-pde

This program was done as an assignment in my graduate Computational Physics course at San Diego State University. It solves the time-dependent Schrodinger equation within a box for two different scenarios, zero and harmonic_well potentials, using the Crank-Nicolson method.

se3ds icon se3ds

This repository hosts the code for our paper, "Simple and Effective Synthesis of Indoor 3D Scenes".

securepuf icon securepuf

An implementation of Lightweight Secure Physically Unclonable Function.

sentiment-analysis icon sentiment-analysis

This tool can be used to analyse the sentiments i.e, Positive or Negative of the review of a product, it can also be trained to analyse the abusive comments.

sentiment_analysis icon sentiment_analysis

Applying a Naive Bayes classifier in order to detect abusive comments based on the Bag-of-Words model. The real-world supervised data from the comment sections of a website are preprocessed to obtain the clean input dataset.

shap icon shap

A game theoretic approach to explain the output of any machine learning model.

siam_pp_20_minitutorial icon siam_pp_20_minitutorial

Jupyter Notebooks for the minitutorial "Combinatorial Optimization on Quantum Computers" at SIAM Conference on Parallel Processing for Scientific Computing (PP20)

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