AIML Projects
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Updated
May 26, 2024 - Jupyter Notebook
AIML Projects
Test-Time Entropy Minimization with Prototype Learning for EEG Signals
Deep Learning Courses
Denoising Diffusion Medical Model (DDMM) on PyTorch for generating datasets of Acute Lymphoblastic Leukemia 🩺💜
Official code release for "CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity"
Single (i) Cell R package (iCellR) is an interactive R package to work with high-throughput single cell sequencing technologies (i.e scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq and Spatial Transcriptomics (ST)).
Model to predict bank customer churn
Neural Network
Official repository for AAAI2024 paper <Unraveling Batch Normalization for Realistic Test-Time Adaptation>.
Leveraging advanced image processing and deep learning, this project classifies plant images using a subset of the Plant Seedlings dataset. The dataset includes diverse plant species captured under varying conditions. This project holds significance within my Master's in Computer Vision at uOttawa (2023).
In this PJ I build a simple Conv2d network and implement some beneficial modifications based on it. Meanwhile, by researching into the BatchNorm algorithm, I verify its benefits on a variety of procedures.
M. Vidal & A. M. Aguilera. Novel whitening approaches in functional settings. Stat, 12(1), e516.
The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.
A CNN model to identify images of plant seedlings.
Tune-Mode ConvBN Blocks For Efficient Transfer Learning
CIFAR10 Dataset.
The open source code for the paper "Block Attention and Switchable Normalization based Deep Learning Framework for Segmentation of Retinal Vessels"
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