Peyman Bateni's repositories
simple-cnaps
Source codes for "Improved Few-Shot Visual Classification" (CVPR 2020), "Enhancing Few-Shot Image Classification with Unlabelled Examples" (WACV 2022), and "Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning" (SSRN Electronic Journal)
multimodal-emotion-analysis-in-conversations
Multi-model analysis of sentiment and emotion in multi-speaker conversations.
neural-sentimental-visual-captioning
Evaluating multiple novel approaches for adjective use in image captioning.
foppl-evaluator
This repository contains the code for the foppl evaluator.
sequential-monte-carlo
Code for a python based implementation of a FOPPL SMC sampler.
a-plus-expert
Source code for the A+ Expert dashboard and client management service.
meta-dataset
A dataset of datasets for learning to learn from few examples
conv-emotion
This repo contains implementation of different architectures for emotion recognition in conversations
cpp_example
A simple example swift-pm for demonstrating c++ interop.
personal-website
Repository for maintaining personal academic web-page!
peymanbateni.github.io
This repository contains my personal academic webpage.
pytorch-classification
Classification with PyTorch.
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
transformer-mgk
This is the public github for our paper "Transformer with a Mixture of Gaussian Keys"