Rohit Lal take2rohit
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NASA IMPACT
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20:15
(UTC -05:00) - rohitlal.com
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Highlights
Stars
Implementation of the Surya Foundation Model and Downstream Tasks for Heliophysics
Benchmark Dataset for Advancing Machine Learning in Heliophysics and Space Weather Prediction
This is my portfolio website of Rohit Lal. (https://rohitlal.com/)
Finetuning Prithvi WxC - Climate Model Parameterization for Gravity Wave Flux
Implementation of the Prithvi WxC Foundation Model and Downstream Tasks
A tool for efficient semi-supervised video object segmentation (great results with minimal manual labor) and a dataset for benchmarking
Source free Single and Multi target Unsupervised Domain Adaptation
Official Code release for Open-Set Multi-Source Multi-Target Domain Adaptation
Official code release for CAFT: Class Aware Frequency Transform for Reducing Domain Gap (accepted at TradiCV Workshop, ICCV 21)
Face Recognition project for automatic door unlock system.
Variational Deep Learning implementations, starting from simple Autoencoders.
Monk is a low code Deep Learning tool and a unified wrapper for Computer Vision.
This repository contains implementations of Quantum Machine Learning algorithms, feature maps, variational circuits and research papers.
IvLabs / Deep-Learning-Based-Stair-Segmentation-and-Behavioral-Cloning-for-Autonomous-Stair-Climbing
Code for "Deep Learning-Based Stair Segmentation and Behavioral Cloning for Autonomous Stair Climbing"
Deep Learning and Computer Vision based Summer Project for the year 2019.
Version 3 of Autonomous Stair Climbing Robot
Implementing trajectory optimization on bipedal system
Resources on various topics being worked on at IvLabs
Contains various architectures and novel paper implementations for Natural Language Processing tasks like Sequence Modelling and Neural Machine Translation.
Deep Learning based pipeline for alignment of a robot with stairs
A one-stop repository for low-code easily-installable object detection pipelines.
Code implementation of Data Efficient Stagewise Knowledge Distillation paper.