I train deep neural networks, debug deep architectures, and build deep learning systems from scratch.
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I train deep neural networks, debug deep architectures, and build deep learning systems from scratch.
This repository studies how residual connections affect optimization stability in deep Transformers. Through controlled experiments and mathematical analysis, it examines gradient propagation, laye…
A fully-connected AutoEncoder for MNIST, implemented from scratch with custom layers, custom IDX dataloader, and research-grade training & visualization pipelines.
Jupyter Notebook
A fully-connected Variational AutoEncoder (VAE) for MNIST, implemented entirely from scratch with custom encoder–decoder architecture, reparameterization trick, handcrafted IDX dataloader, and rese…
Jupyter Notebook
PyTorch implementation of Deep Convolutional Generative Adversarial Networks (DCGAN) trained on the CelebA dataset
Python