Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Network…

Dilated RNNs in pytorch

e3d-lstm; Eidetic 3D LSTM A Model for Video Prediction and Beyond

Integrating Mamba/SSMs with Transformer for Enhanced Long Context and High-Quality Sequence Modeling

This repository contains my solutions to the assignments for Stanford's CS231n "Convolutional Neural Networks for Visual Recognition" (Spring 2020).

[CVPR'24 Spotlight] The official implementation of "State Space Models for Event Cameras"

Handwriting Synthesis and Prediction - PyTorch Implementation

Implementation of Griffin from the paper: "Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models"

A lightweight but powerful library to build token indices for NLP tasks, compatible with major Deep Learning frameworks like PyTorch and Tensorflow.

[ACM Computing Surveys'23] Implementations or refactor of some temporal link prediction/dynamic link prediction methods and summary of related open resources for survey paper "Temporal Link Prediction: A Unified Framework, Taxonomy, and Review" which has been accepted by ACM Computing Surveys.

Implementation of a modular, high-performance, and simplistic mamba for high-speed applications

This repo contains my work & The code base for this TensorFlow Developer specialization offered by deeplearning.AI

Deep Recurrent Neural Networks (RNNs) for Time-Series Prediction

An open source community implementation of the model from "DIFFERENTIAL TRANSFORMER" paper by Microsoft.

Implementation of a Hierarchical Mamba as described in the paper: "Hierarchical State Space Models for Continuous Sequence-to-Sequence Modeling"

AI@UCF's custom-made course, organized by semesters

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks..

This repository is for the Session held in International Conference on Data Management, Analytics and Innovation, New Delhi 2020

Welcome to Prometheus, the revolutionary AI model that allows you to generate DNA sequences for any creature you can imagine. Whether it’s a pink panda, an elephant-sized turtle, or a completely new lifeform from your wildest dreams, Prometheus decodes the mystery of biology and synthesizes genetic blueprints with precision.

The system enables sophisticated coordination of multiple drones through natural language commands, visual inputs, and real-time environmental data.