Jason Ken Adhinarta (jasonkena)

jasonkena

Geek Repo

Company:Boston College

Location:Chestnut Hill

Home Page:https://jasonkena.github.io/

Github PK Tool:Github PK Tool


Organizations
bc-cv
emmerich-research
M3DV

Jason Ken Adhinarta's repositories

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smmo_pvp_tool

https://revogen.xyz/

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AxonEM-challenge

utility code for AxonEM challenge

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cellpose

a generalist algorithm for cellular segmentation with human-in-the-loop capabilities

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cloud-volume

Read and write Neuroglancer datasets programmatically.

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dask

Parallel computing with task scheduling

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dask-jobqueue

Deploy Dask on job schedulers like PBS, SLURM, and SGE

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dgcnn.pytorch

A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)

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distributed

A distributed task scheduler for Dask

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images

Community maintained container images to use with toolbx (and distrobox)

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jasonkena_cv

My CV written using jinja2 to render yaml as LaTeX

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nerf-pytorch

A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.

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normalizing-flows

PyTorch implementation of normalizing flow models

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pointcnn_pytorch

PointCNN baseline for the RibSegv2 challenge

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Pointnet_Pointnet2_pytorch

PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.

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PyTorch-VAE

A Collection of Variational Autoencoders (VAE) in PyTorch.

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pytorch_connectomics

PyTorch Connectomics: segmentation toolbox for EM connectomics

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qmk_firmware

Open-source keyboard firmware for Atmel AVR and Arm USB families

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RibSeg

[MICCAI'21] RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT Scans

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STU-Net

The largest pre-trained medical image segmentation model (1.4B parameters) based on the largest public dataset (>100k annotations), up until April 2023.

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Track-Anything

Track-Anything is a flexible and interactive tool for video object tracking and segmentation, based on Segment Anything, XMem, and E2FGVI.

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vim-arsync

vim plugin for async synchronisation of remote files and local files using rsync

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weave

Weave, developed by the team at Weights and Biases, is a new open-source toolkit designed for performant, interactive data exploration. Our mission is to equip Machine Learning practitioners with the best tools to turn data into insights quickly and easily.

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zict

Useful Mutable Mappings

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