Contextual Encoder-Decoder Network for Visual Saliency Prediction [Neural Networks 2020]
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Updated
May 28, 2024 - Python
Contextual Encoder-Decoder Network for Visual Saliency Prediction [Neural Networks 2020]
X-Llama🦙 is an Extensible advanced language model framework, inspired by the original Llama model.
Official implementation for the paper: "Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering""
An unofficial implementation of TubeViT in "Rethinking Video ViTs: Sparse Video Tubes for Joint Image and Video Learning"
A Collection of Variational Autoencoders (VAE) in PyTorch.
Implementation of the paper "Improved DeepFake Detection Using Whisper Features"
👨🎨 DDPM, and High-Resolution Image Synthesis with Latent Diffusion Models, papers implementation from scratch using pytorch.
My Implementations' Archive
ZeroRF: Fast Sparse View 360° Reconstruction with Zero Pretraining
Latent diffusion model following Umar Jamil's tutorial https://youtu.be/ZBKpAp_6TGI?si=Fa822KYeOP_2LWdr https://github.com/hkproj/pytorch-stable-diffusion
Automatically generating language descriptions for remote sensing images has emerged as a significant research area within the field of remote sensing. This project focuses on attention-based captioning methods, which are a prominent class of deep learning-based techniques for generating captions.
Attention is all you need implementation
Code for paper "A Semi-Automated Usability Evaluation Framework for Interactive Image Segmentation Systems"
Experiment, data, and analysis code for "Text embedding models yield high-resolution insights into conceptual knowledge from short multiple-choice quizzes" by Paxton C. Fitzpatrick, Andrew C. Heusser, and Jeremy R. Manning
Simple Implementation of Rotary Positional Embeddings (RoPE) and Sinusoidal Positional Embeddings in JAX
Personal Implementation of Deep Learning Algorithms
(ViT) Vision Image Transformer PyTorch Implementation
Handwriting generation and handwriting synthesis as described in Alex Graves's paper https://arxiv.org/abs/1308.0850. Pytorch implementation.
Code for the paper "Combining Gradients and Probabilities for Heterogeneours Approximation of Neural Networks"
Naive implementations of deep reinforcement learning algorithms
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