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Hi there 👋 I'm Aditya Kane

🔬 I primarily work on vision and language problems in deep learning.

👨‍💻 Currently working on multimodal large language models and making ViTs more efficient. Making those GPUs go brrrr!

📚 Second year MS CS student at Georgia Institute of Technology.

I ❤️ open source.

🌐 My coordinates are: adityakane2001.github.io

Feel free to reach out if you would like to collaborate!

Connect with me:

Aditya Kane's Projects

awesomo icon awesomo

Cool open source projects written in C, C++, Clojure, Lisp, Elixir, Erlang, Elm, Golang, Haskell, JavaScript, Lua, OCaml, Python, R, Ruby, Rust, Scala, etc.

bpjdet icon bpjdet

Codes for my paper "Body-Part Joint Detection and Association via Extended Object Representation"

contra-ood icon contra-ood

Source code for paper "Contrastive Out-of-Distribution Detection for Pretrained Transformers", EMNLP 2021

cookie icon cookie

A see-through automatic differentiation library.

crypto icon crypto

A nano library in C++ made for quick encryption and decryption

db icon db

A PyTorch implementation of "Real-time Scene Text Detection with Differentiable Binarization".

dbnet.pytorch icon dbnet.pytorch

A pytorch re-implementation of Real-time Scene Text Detection with Differentiable Binarization

deepunkid icon deepunkid

Deep Unknown Intent Detection with Margin Loss (ACL2019)

deepvision icon deepvision

PyTorch and TensorFlow/Keras image models with automatic weight conversions and equal API/implementations - Vision Transformer (ViT), ResNetV2, EfficientNetV2, (planned...) DeepLabV3+, ConvNeXtV2, YOLO, NeRF, etc.

dim icon dim

Distilling dataset into generative models

dino icon dino

[ICLR 2023] Official implementation of the paper "DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection"

dl4cv icon dl4cv

Series of notebooks accompanying the book "Practical Deep Learning for Computer Vision with Python" to get you from walking to running in CV with Keras/TensorFlow, KerasCV and PyTorch

domainbed icon domainbed

DomainBed is a suite to test domain generalization algorithms

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