Pinned Repositories
A_Dynamic_Topic_Modeling_comparison
This repository presents a comprehensive dissertation project from University College London's Business Analytics MSc program, featuring an in-depth assessment and comparison of four dynamic topic modelling frameworks - Non-Negative Matrix Factorization (NMF), Latent Dirichlet Allocation (LDA), Top2Vec, and BERTopic.
Complex-PINNs-for-NLSE
This repository hosts a project utilizing Complex Physics-Informed Neural Networks (Complex PINNs) to solve the Nonlinear Schrödinger Equation (NLSE)
Differential_Equation_DL
This repository, titled 'MachineLearning_for_Differential_Equations', contains a comprehensive approach to solving Ordinary Differential Equations (ODEs) using machine learning techniques.
ips_MaxRiffiAslett
This repository contains the code for my dissertation, which adapts the IPS approach from benbergner/ips. IPS is a simple patch-based method that decouples memory consumption from input size, enabling efficient processing of high-resolution images without running out of memory.
Neural-Network-Implementation-from-Scratch
This repository features a pure NumPy implementation of a neural network, built from scratch for educational purposes. It's part of my coursework at University College London (UCL) and serves as a hands-on project to deepen understanding of the fundamental principles behind neural networks.
NLI-Baseline-PyTorch
This repository provides a comprehensive collection of PyTorch-based baseline models for Natural Language Inference (NLI) tasks.
PDE-Discovery-SparseRegression
PDE Discovery with Sparse Regression: A repository containing code for discovering partial differential equation (PDE) terms using sparse regression techniques. It includes a script that trains a neural network to approximate PDE solutions and utilizes sparse regression with Lasso regularization to identify the underlying PDE terms.
PINNs-for-PDEs
This repository contains an implementation of a Physics-Informed Neural Network (PINN) to solve a specific Partial Differential Equation (PDE).
Seq2Seq-Transformer
Using Pytorch's nn.Transformer module to create an english to french neural machine translation model.
TensorFlow-LS-InfoGAN
TensorFlow-LS-InfoGAN is a TensorFlow-based repo for generating MNIST digits using LS-GAN and InfoGAN, promoting image quality and feature disentanglement.
MRiffiAslett's Repositories
MRiffiAslett/Complex-PINNs-for-NLSE
This repository hosts a project utilizing Complex Physics-Informed Neural Networks (Complex PINNs) to solve the Nonlinear Schrödinger Equation (NLSE)
MRiffiAslett/Differential_Equation_DL
This repository, titled 'MachineLearning_for_Differential_Equations', contains a comprehensive approach to solving Ordinary Differential Equations (ODEs) using machine learning techniques.
MRiffiAslett/PDE-Discovery-SparseRegression
PDE Discovery with Sparse Regression: A repository containing code for discovering partial differential equation (PDE) terms using sparse regression techniques. It includes a script that trains a neural network to approximate PDE solutions and utilizes sparse regression with Lasso regularization to identify the underlying PDE terms.
MRiffiAslett/PINNs-for-PDEs
This repository contains an implementation of a Physics-Informed Neural Network (PINN) to solve a specific Partial Differential Equation (PDE).
MRiffiAslett/A_Dynamic_Topic_Modeling_comparison
This repository presents a comprehensive dissertation project from University College London's Business Analytics MSc program, featuring an in-depth assessment and comparison of four dynamic topic modelling frameworks - Non-Negative Matrix Factorization (NMF), Latent Dirichlet Allocation (LDA), Top2Vec, and BERTopic.
MRiffiAslett/ips_MaxRiffiAslett
This repository contains the code for my dissertation, which adapts the IPS approach from benbergner/ips. IPS is a simple patch-based method that decouples memory consumption from input size, enabling efficient processing of high-resolution images without running out of memory.
MRiffiAslett/Neural-Network-Implementation-from-Scratch
This repository features a pure NumPy implementation of a neural network, built from scratch for educational purposes. It's part of my coursework at University College London (UCL) and serves as a hands-on project to deepen understanding of the fundamental principles behind neural networks.
MRiffiAslett/NLI-Baseline-PyTorch
This repository provides a comprehensive collection of PyTorch-based baseline models for Natural Language Inference (NLI) tasks.
MRiffiAslett/Postgres-ETL-Pipeline
This project implements an ETL (Extract, Transform, Load) pipeline using Python and PostgreSQL for Sparkify, a music streaming service. The pipeline extracts data from JSON files, transforms it into a star schema database model.
MRiffiAslett/Seq2Seq-Transformer
Using Pytorch's nn.Transformer module to create an english to french neural machine translation model.
MRiffiAslett/TensorFlow-LS-InfoGAN
TensorFlow-LS-InfoGAN is a TensorFlow-based repo for generating MNIST digits using LS-GAN and InfoGAN, promoting image quality and feature disentanglement.
MRiffiAslett/Analysis-21-05-2024
MRiffiAslett/DigitNeural-network-FromScratch
MRiffiAslett/Elevating-Airline-Analytics-A-Comprehensive-Model-for-Flight-Disruption-Prediction
MRiffiAslett/grasdf
MRiffiAslett/ips_attention_masking
MRiffiAslett/jjjjkl-lkj
MRiffiAslett/MT5751---Project-1-Distance-Sampling
MT5751 - Project 1 Distance Sampling
MRiffiAslett/MT5758_III_230022790
MRiffiAslett/nji-lkjkl-
MRiffiAslett/Notebook-MT5751---Project-3-Occupancy-Estimation
MRiffiAslett/PortfolioOptimisation
This repository showcases the implementation of deep learning techniques in the field of finance, focusing on return prediction and portfolio construction
MRiffiAslett/Web_Scapper
This repository contains scripts and data for scraping articles from the GoV.UK website. The project aims to extract the date, content, and title of approximately 6000 articles from GoV.UK for further analysis. The extracted data is stored in JSON format, and additional scripts are provided for preprocessing and generating visualizations.