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Akshay Subramanian's Projects

mask_rcnn icon mask_rcnn

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

ml-for-science icon ml-for-science

List of papers applying Machine Learning to scientific problems that were discussed in our weekly discussion sessions. Our primary focus is on materials science, molecular optimization and drug discovery.

moldqn-pytorch icon moldqn-pytorch

A PyTorch Implementation of "Optimization of Molecules via Deep Reinforcement Learning".

molecular-vae icon molecular-vae

Pytorch implementation of the paper "Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules"

moses icon moses

Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models

omniport-docs icon omniport-docs

The Sphinx documentation of the one true portal for any and every educational institute

reinvent icon reinvent

Molecular De Novo design using Recurrent Neural Networks and Reinforcement Learning

student-assistant icon student-assistant

A chatbot built using DialogFlow to schedule and answer questions on day to day jobs

tape icon tape

Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.

torchchem icon torchchem

An experimental repo for experimenting with PyTorch models

twint icon twint

An advanced Twitter scraping & OSINT tool written in Python that doesn't use Twitter's API, allowing you to scrape a user's followers, following, Tweets and more while evading most API limitations.

uncertainty_guided_optimization icon uncertainty_guided_optimization

Official repository for the paper "Improving black-box optimization in VAE latent space using decoder uncertainty" (Pascal Notin, José Miguel Hernández-Lobato, Yarin Gal)

voicemap icon voicemap

Identifying people from small audio fragments

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